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Tarkhan, Mahdi, Saeed Bagheri Shouraki i Seyed Hossein Khasteh. "A novel hardware implementation of IDS method". IEICE Electronics Express 6, nr 23 (2009): 1626–30. http://dx.doi.org/10.1587/elex.6.1626.
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Paul, Morgan. "Looking to the Future". Pathfinder: A Canadian Journal for Information Science Students and Early Career Professionals 4, nr 1 (8.09.2023): 54–67. http://dx.doi.org/10.29173/pathfinder71.
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This article explores the concept of Indigenous Data Sovereignty (IDS) in Canada, examining its barriers, resources, implementation, and policy implications. While not an exhaustive list of all IDS-related policies, the article focuses on key definitions, successful implementations, support programs and resources, and outdated policies that hinder IDS and Indigenous governance practices. Through a First Nations lens, the paper highlights the importance of Indigenous People's control over data and knowledge about their communities and lands. It discusses the challenges of implementing IDS within non-Indigenous organizations and communities, including financial constraints and the influence of colonial policies. The article also addresses the impact of IDS on Indigenous self-determination, emphasizing the need for government and educational institutions to support IDS practices. Additionally, it explores the First Nations' principles of Ownership, Control, Access, and Possession (OCAP) as an example of successful IDS implementations. The paper acknowledges the role of data sovereignty in reconciliation frameworks and highlights resources such as the International Work Group for Indigenous Affairs (IWGIA) and the Global Indigenous Data Alliance (GIDA) that advocate for IDS and Indigenous self-governance. The conclusion emphasizes the ongoing need for support, collaboration, and the mobilization of UNDRIP and TRC frameworks to ensure the success of IDS and the amendment of colonial policies.
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Mizutani, Masayoshi, Shin Shirahata, Masaki Minami i Jun Murai. "The design and implementation of session-based IDS". Electronics and Communications in Japan (Part I: Communications) 89, nr 3 (marzec 2006): 46–58. http://dx.doi.org/10.1002/ecja.20251.
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Bush-Mecenas, Susan, Julie A. Marsh i Katharine O. Strunk. "Guiding Principals: Middle-Manager Coaching and Human-Capital Reform". Teachers College Record: The Voice of Scholarship in Education 122, nr 10 (październik 2020): 1–50. http://dx.doi.org/10.1177/016146812012201004.
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Background/Context School leaders are central to state and district human-capital reforms (HCRs), yet they are rarely equipped with the skills to implement new evaluation, professional development, and personnel data systems. Although districts increasingly offer principals coaching and training, there has been limited empirical work on how these supports influence principals’ HCR-related practices. Purpose Drawing on a two-year, mixed-methods study in the Los Angeles Unified School District (LAUSD), this article examines the role of principal supervisors in HCRs. We ask: What role did principal supervisors (Instructional Directors [IDs]) play in the implementation of human-capital reforms? What did high-quality coaching on the part of IDs look like in this context? Research Design Our two-part analysis draws upon survey and interview data. First, we conducted descriptive analyses and significance testing using principal and ID survey data to examine the correlations among principals’ ratings of ID coaching quality, ID coaching practices, and principals’ implementation of HCRs. Second, we conducted in-depth interviews, using a think-aloud protocol, with two sets of IDs—those consistently highly-rated and those with mixed ratings—who were identified using principals’ reports of coaching quality. Following interview coding, we created various case-ordered metamatrix displays to analyze our qualitative data in order to identify patterns in coaching strategy and approach across IDs, content, and contexts. Findings First, our survey data indicate that receiving high-quality coaching from IDs is correlated with stronger principal support for and implementation of HCRs. Our survey findings further illustrate that IDs support a wide range of principals’ HCR activities. Second, our think-aloud interviews with case IDs demonstrate that coaching strategy and approach vary between consistently highly-rated and mixed-rated coaches: Consistently highly-rated IDs emphasize the importance of engaging in, or defining HCR problems as, joint work alongside principals, while mixed-rated IDs often emphasize the use of tools to guide principal improvement. We find that, on the whole, the consistently highly-rated IDs in our sample employ a nondirective approach to coaching more often than mixed-rated coaches. Conclusions These findings contribute to a growing literature on the crucial role of principal supervisors as coaches to improve principals’ instructional leadership and policy implementation. While exploratory, this study offers the first steps toward building greater evidence of the connections between high-quality coaching and policy implementation, and it may have implications for the design and implementation of professional development for principal supervisors and the selection and placement of supervisors with principals.
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Merrikh-Bayat, Farnood, Saeed Bagheri Shouraki i Ali Rohani. "Memristor Crossbar-Based Hardware Implementation of the IDS Method". IEEE Transactions on Fuzzy Systems 19, nr 6 (grudzień 2011): 1083–96. http://dx.doi.org/10.1109/tfuzz.2011.2160024.
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Ben Charhi, Youssef, Nada Mannane, Elmahdi Bendriss i Regragui Boubker. "Behavioral Analysis Approach for Likelihood Determination in Cloud IDS: Implementation Architecture". International Journal of Mobile Devices, Wearable Technology, and Flexible Electronics 9, nr 1 (styczeń 2018): 36–57. http://dx.doi.org/10.4018/ijmdwtfe.2018010103.
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Cyberattacks present a ubiquitous threat to an enterprise's information in Cloud Computing assets and must be properly controlled. The use of the current generation of IDS have various limitations on their performance making them not effective for cloud computing security and could generate a huge number of false-positive alarms. Analyzing intrusion based on attack patterns and risk assessment has demonstrated its efficiency in reducing the number of false alarms and optimizing the IDS performances. However, the use of the same value of likelihood makes the approach lack a real risk value determination. This article intends to present a new probabilistic and behavioral approach for likelihood determination to quantify attacks in cloud environment. With the main task to increase the efficiency of IDS and decrease the number of alarms. Experimental results show that the approach is superior to the state-of-the-art approach for intrusion detection in the cloud.
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Bouchet, Flavien, Vincent Le Moing, Delphine Dirand, François Cros, Alexi Lienard, Jacques Reynes, Laurent Giraudon i David Morquin. "Effectiveness and Acceptance of Multimodal Antibiotic Stewardship Program: Considering Progressive Implementation and Complementary Strategies". Antibiotics 9, nr 12 (27.11.2020): 848. http://dx.doi.org/10.3390/antibiotics9120848.
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Multiple modes of interventions are available when implementing an antibiotic stewardship program (ASP), however, their complementarity has not yet been assessed. In a 938-bed hospital, we sequentially implemented four combined modes of interventions over one year, centralized by one infectious diseases specialist (IDS): (1) on-request infectious diseases specialist consulting service (IDSCS), (2) participation in intensive care unit meetings, (3) IDS intervention triggered by microbiological laboratory meetings, and (4) IDS intervention triggered by pharmacist alert. We assessed the complementarity of the different cumulative actions through quantitative and qualitative analysis of all interventions traced in the electronic medical record. We observed a quantitative and qualitative complementarity between interventions directly correlating to a decrease in antibiotic use. Quantitatively, the number of interventions has doubled after implementation of IDS intervention triggered by pharmacist alert. Qualitatively, these kinds of interventions led mainly to de-escalation or stopping of antibiotic therapy (63%) as opposed to on-request IDSCS (32%). An overall decrease of 14.6% in antibiotic use was observed (p = 0.03). Progressive implementation of the different interventions showed a concrete complementarity of these actions. Combined actions in ASPs could lead to a significant decrease in antibiotic use, especially regarding critical antibiotic prescriptions, while being well accepted by prescribers.
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Mahesh T R, V Vivek i Vinoth Kumar. "Implementation of Machine Learning-Based Data Mining Techniques for IDS". International Journal of Information Technology, Research and Applications 2, nr 1 (31.03.2023): 7–13. http://dx.doi.org/10.59461/ijitra.v2i1.23.
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The internet is essential for ongoing contact in the modern world, yet its effectiveness might lessen the effect known as intrusions. Any action that negatively affects the targeted system is considered an intrusion. Network security has grown to be a major issue as a result of the Internet's rapid expansion. The Network Intrusion Detection System (IDS), which is widely used, is the primary security defensive mechanism against such hostile assaults. Data mining and machine learning technologies have been extensively employed in network intrusion detection and prevention systems to extract user behaviour patterns from network traffic data. Association rules and sequence rules are the main foundations of data mining used for intrusion detection. Given the Auto encoder algorithm's traditional method's bottleneck of frequent itemsets mining, we provide a Length-Decreasing Support to Identify Intrusion based on Data Mining, which is an upgraded Data Mining Techniques based on Machine Learning for IDS. Based on test results, it appears that the suggested strategy is successful
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Kim, Song-Mok, i Seungyoung Park. "Real-Time Implementation of Bi-directional GPT-based CAN IDS Using Jetson Nano". Journal of Digital Contents Society 24, nr 11 (30.11.2023): 2871–79. http://dx.doi.org/10.9728/dcs.2023.24.11.2871.
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Silva, Rui Filipe, Raul Barbosa i Jorge Bernardino. "Intrusion Detection Systems for Mitigating SQL Injection Attacks". International Journal of Information Security and Privacy 14, nr 2 (kwiecień 2020): 20–40. http://dx.doi.org/10.4018/ijisp.2020040102.
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Databases are widely used by organizations to store business-critical information, which makes them one of the most attractive targets for security attacks. SQL Injection is the most common attack to webpages with dynamic content. To mitigate it, organizations use Intrusion Detection Systems (IDS) as part of the security infrastructure, to detect this type of attack. However, the authors observe a gap between the comprehensive state-of-the-art in detecting SQL Injection attacks and the state-of-practice regarding existing tools capable of detecting such attacks. The majority of IDS implementations provide little or no protection against SQL Injection attacks, with exceptions like the tools Bro and ModSecurity. In this article, the authors compare these tools using the CSIC dataset in order to examine the state-of-practice in database protection from SQL Injection attacks, identifying the main characteristics and implementation details needed for IDSs to successfully detect such attacks. The experiments indicate that signature-based IDS provide the greatest coverage against SQL Injection.
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Otoum, Safa, Burak Kantarci i Hussein Mouftah. "A Comparative Study of AI-Based Intrusion Detection Techniques in Critical Infrastructures". ACM Transactions on Internet Technology 21, nr 4 (22.07.2021): 1–22. http://dx.doi.org/10.1145/3406093.
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Volunteer computing uses Internet-connected devices (laptops, PCs, smart devices, etc.), in which their owners volunteer them as storage and computing power resources, has become an essential mechanism for resource management in numerous applications. The growth of the volume and variety of data traffic on the Internet leads to concerns on the robustness of cyberphysical systems especially for critical infrastructures. Therefore, the implementation of an efficient Intrusion Detection System for gathering such sensory data has gained vital importance. In this article, we present a comparative study of Artificial Intelligence (AI)-driven intrusion detection systems for wirelessly connected sensors that track crucial applications. Specifically, we present an in-depth analysis of the use of machine learning, deep learning and reinforcement learning solutions to recognise intrusive behavior in the collected traffic. We evaluate the proposed mechanisms by using KDD’99 as real attack dataset in our simulations. Results present the performance metrics for three different IDSs, namely the Adaptively Supervised and Clustered Hybrid IDS (ASCH-IDS), Restricted Boltzmann Machine-based Clustered IDS (RBC-IDS), and Q-learning based IDS (Q-IDS), to detect malicious behaviors. We also present the performance of different reinforcement learning techniques such as State-Action-Reward-State-Action Learning (SARSA) and the Temporal Difference learning (TD). Through simulations, we show that Q-IDS performs with detection rate while SARSA-IDS and TD-IDS perform at the order of .
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Ha, Jaecheol. "Preprocessor Implementation of Open IDS Snort for Smart Manufacturing Industry Network". Journal of the Korea Institute of Information Security and Cryptology 26, nr 5 (31.10.2016): 1313–22. http://dx.doi.org/10.13089/jkiisc.2016.26.5.1313.
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Dewi Paramitha, Ida Ayu Shinta, Gusti Made Arya Sasmita i I. Made Sunia Raharja. "Analisis Data Log IDS Snort dengan Algoritma Clustering Fuzzy C-Means". Majalah Ilmiah Teknologi Elektro 19, nr 1 (15.10.2020): 95. http://dx.doi.org/10.24843/mite.2020.v19i01.p14.
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Snort is one of open source IDS to detect intrusion or potentially malicious activity on network traffic. Snort will give alert for every detected intrusion and write the alerts in log. Log data in IDS Snort will help network administrator to analyze the vulnerability of network security system. Clustering algorithm such as FCM can be used to analyze the log data of IDS Snort. Implementation of the algorithm is based on Python 3 and aims to cluster alerts in log data into 4 risk categories, such as low, medium, high, and critical. The outcome of this analysis is to show cluster results of FCM and to visualize the types of attacks that IDS Snort has successfully detected. Evaluation process is done by using Modified Partition Coefficient (MPC) to determine the validity of FCM.
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Agarwal, Nancy, i Syed Zeeshan Hussain. "A Closer Look at Intrusion Detection System for Web Applications". Security and Communication Networks 2018 (14.08.2018): 1–27. http://dx.doi.org/10.1155/2018/9601357.
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Intrusion Detection System (IDS) acts as a defensive tool to detect the security attacks on the web. IDS is a known methodology for detecting network-based attacks but is still immature in monitoring and identifying web-based application attacks. The objective of this research paper is to present a design methodology for efficient IDS with respect to web applications. In this paper, we present several specific aspects which make it challenging for an IDS to monitor and detect web attacks. The article also provides a comprehensive overview of the existing detection systems exclusively designed to observe web traffic. Furthermore, we identify various dimensions for comparing the IDS from different perspectives based on their design and functionalities. We also propose a conceptual framework of a web IDS with a prevention mechanism to offer systematic guidance for the implementation of the system. We compare its features with five existing detection systems, namely, AppSensor, PHPIDS, ModSecurity, Shadow Daemon, and AQTRONIX WebKnight. This paper will highly facilitate the interest groups with the cutting-edge information to understand the stronger and weaker sections of the domain and provide a firm foundation for developing an intelligent and efficient system.
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Ryan, Nessa E., Bernadette Boden-Albala, Gabriel Ganyaglo i Alison El Ayadi. "4112 Tools for Self-Management of Obstetric Fistula in Low and Middle-income Countries: A Qualitative Study Exploring Pre-implementation Barriers and Facilitators among Global Stakeholders". Journal of Clinical and Translational Science 4, s1 (czerwiec 2020): 149–50. http://dx.doi.org/10.1017/cts.2020.440.
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OBJECTIVES/GOALS: Insertable devices (IDs) for obstetric fistula (OF) management are feasible, acceptable, but not accessible; implementation determinants in low and middle-income countries (LMICs) are unknown. Thus, the purpose of this study was to understand pre-adoption facilitators and barriers among global stakeholders for a therapeutic ID for OF in LMICs. METHODS/STUDY POPULATION: Stakeholders, including researchers (n = 11), clinicians (n = 4), government officials (n = 2), and administrators (n = 4), were purposefully identified from various sectors involved in understanding and addressing the needs of women with OF: clinical care, academia, international health, civil society, and government. Twenty-one individuals were interviewed about their perceptions of IDs for OF self-management and their implementation. Interviews were audio-recorded and transcribed. The Consolidated Framework for Implementation Research (CFIR) guided data collection and analysis. Thematic analyses were carried out within Nvivo v.12. RESULTS/ANTICIPATED RESULTS: Determinants of implementation of an ID for OF self-management (by CFIR domain) include: (1) intervention characteristics—relative advantage and cost; (2) individual characteristics—knowledge and beliefs about the innovation; (3) inner setting-- organizational culture, implementation climate, tension for change, and compatibility; (4) outer setting-- patient needs and resources and external policy and incentives; (5) process—opinion leaders and collaboration. Facilitators include: tension for change for low-cost, accessible IDs; relative advantage over existing tools; development of partnerships; and identification of implementation champions. Barriers include: need for educational strategies to encourage clinical provider acceptability; lack of evidence of the optimal beneficiary. DISCUSSION/SIGNIFICANCE OF IMPACT: Tools for therapeutic OF self-management could be integrated into comprehensive OF programming. Employing the CFIR as an overarching typology allows for comparison across contexts and settings where OF care occurs and may be useful for clinicians, researchers, and policy-makers interested in implementing IDs for OF self-management in LMICs. CONFLICT OF INTEREST DESCRIPTION: I am working with colleagues at the non-profit Restore Health on developing an insertable cup for therapeutic self-management of obstetric fistula in LMICs
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Kim, Youbin, i Jaehwan Lee. "Implementation Guide and Evaluation of IAP Process for Convergence Product Design". Journal of Industrial Design Studies 51 (31.03.2020): 45–52. http://dx.doi.org/10.37254/ids.2020.03.51.05.45.
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Pietro Spadaccino i Francesca Cuomo. "Intrusion detection systems for IoT: Opportunities and challenges offered by edge computing". ITU Journal on Future and Evolving Technologies 3, nr 2 (22.09.2022): 408–20. http://dx.doi.org/10.52953/wnvi5792.
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Key components of current cybersecurity methods are the Intrusion Detection Systems (IDSs), where different techniques and architectures are applied to detect intrusions. IDSs can be based either on cross-checking monitored events with a database of known intrusion experiences, known as signature-based, or on learning the normal behavior of the system and reporting whether anomalous events occur, named anomaly-based. This work is dedicated to the application of IDS to the Internet of Things (IoT) networks, where also edge computing is used to support IDS implementation. Specific attention is given to IDSs which leverage device classification at the edge. New challenges that arise when deploying an IDS in an edge scenario are identified and remedies are proposed.
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Mudaranthakam, Dinesh Pal, Colin Cernik, Leslie Curtis, Blake Griffith, Jinxiang Hu, Jo Wick, Jeffrey Thompson i in. "Utilization of Technology to Improve Efficiency in Investigational Drug Management Processes". Journal of Pharmacy Technology 36, nr 2 (22.01.2020): 84–90. http://dx.doi.org/10.1177/8755122519900049.
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Background: Background: An investigational pharmacy is responsible for all tasks related to receiving, storing, and dispensing of any investigational drugs. Traditional methods of inventory and protocol tracking on paper binders are very tedious and could be error-prone. Objective: To evaluate the utilization of the IDS to efficiently manage the inventory within an investigational Pharmacy. We hypothesize that the IDS will reduce the drug processing time. Methods: Our pharmacy tracked the drug processing time before and after using the IDS including the receiving, dispensing, and inventory. As part of the receiving the study drug pharmacists tracked the time it took a pharmacist to complete the tasks of logging the study drug before and after the implementation of the IDS system. In addition, the pharmacy also timed the process for drug dispensing and a full investigational drug inventory check. Wilcoxon signed-rank test was used to compare the difference in the meantime of total processing before and after the IDS. Results: Utilization of the IDS system showed significant reduction in processing time, and improvement of efficiency in inventory management. Additionally, the usability survey of the IDS demonstrated that the IDS system helped pharmacists capture data consistently across every clinical trial. Conclusion: Our results demonstrates how technology helps pharmacists to focus on their actual day to day medication-related tasks rather than worrying about other operational aspects. Informatics team continues to further enhance the features such as monitor portal, and features related to finance – generation of invoices, billing reconciliation, etc.
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Mahbooba, Basim, Radhya Sahal, Wael Alosaimi i Martin Serrano. "Trust in Intrusion Detection Systems: An Investigation of Performance Analysis for Machine Learning and Deep Learning Models". Complexity 2021 (8.03.2021): 1–23. http://dx.doi.org/10.1155/2021/5538896.
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To design and develop AI-based cybersecurity systems (e.g., intrusion detection system (IDS)), users can justifiably trust, one needs to evaluate the impact of trust using machine learning and deep learning technologies. To guide the design and implementation of trusted AI-based systems in IDS, this paper provides a comparison among machine learning and deep learning models to investigate the trust impact based on the accuracy of the trusted AI-based systems regarding the malicious data in IDs. The four machine learning techniques are decision tree (DT), K nearest neighbour (KNN), random forest (RF), and naïve Bayes (NB). The four deep learning techniques are LSTM (one and two layers) and GRU (one and two layers). Two datasets are used to classify the IDS attack type, including wireless sensor network detection system (WSN-DS) and KDD Cup network intrusion dataset. A detailed comparison of the eight techniques’ performance using all features and selected features is made by measuring the accuracy, precision, recall, and F1-score. Considering the findings related to the data, methodology, and expert accountability, interpretability for AI-based solutions also becomes demanded to enhance trust in the IDS.
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LeBrón, Alana M. W., Keta Cowan, William D. Lopez, Nicole L. Novak, Maria Ibarra-Frayre i Jorge Delva. "The Washtenaw ID Project: A Government-Issued ID Coalition Working Toward Social, Economic, and Racial Justice and Health Equity". Health Education & Behavior 46, nr 1_suppl (24.09.2019): 53S—61S. http://dx.doi.org/10.1177/1090198119864078.
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Introduction. The policing of identities through policies that restrict access to IDs issued by U.S. governmental entities disparately affects communities of color; communities who identify as low-income, immigrant, older, and/or transgender; and community members who experience chronic mental illness, housing instability, or incarceration. Yet government-issued IDs are increasingly needed to access health-promoting resources such as housing, banking, social services, and health care, and in interactions with law enforcement. Methods. Since 2012, the Washtenaw ID Project’s coalition-building process has involved communities affected by restrictive ID policies, advocates, and institutional stakeholders to enact community and systems change regarding inequities in government-issued IDs. We discuss the coalition-building process that culminated in the implementation of a photo ID issued by Washtenaw County government as a policy change strategy. We also highlight the community-academic research partnership evaluating the effectiveness of the Washtenaw ID in order to ensure equity in Washtenaw ID access and acceptance. Results. In 2015, 77% of Washtenaw ID holders reported having no other locally accepted ID. At follow-up, Washtenaw ID holders reported favorable Washtenaw ID acceptance rates in several domains (e.g., health care, school), but not when accessing banking services and housing. Additionally, community discussions suggested racial inequities in carding and ID acceptance. We discuss next steps for policy improvement to ensure equitable impact of the ID. Conclusions. Without national policy reform instating access to government-issued IDs for all, the social movement to establish local IDs may improve access to health-related resources contingent on having an ID. Careful attention must be paid to community organizing processes, policy implementation, and evaluation to ensure equity.
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Lodhi, Mala Bharti, Vineet Richhariya i Mahesh Parmar. "AN IMPLEMENTATION OF IDS IN A HYBRID APPROACH AND KDD CUP DATASET". International Journal of Research -GRANTHAALAYAH 2, nr 3 (31.12.2014): 1–9. http://dx.doi.org/10.29121/granthaalayah.v2.i3.2014.3055.
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Now in these days due to rapidly increasing network applications the data and privacy security in network is a key challenge. In order to provide effective and trustable security for network, intrusion detection systems are helpful. The presented study is based on the IDS system design for network based anomaly detection. Thus this system requires an efficient and appropriate classifier by which the detection rate of intrusions using KDD CPU dataset can be improved. Due to study there is various kind of data mining based, classification and pattern detection techniques are available. These techniques are promising for detecting network traffic pattern more accurately. On the other hand recently developed the hybrid models are providing more accurate classification. Thus a hybrid intrusion system is presented in this proposed work. That provides a significant solution even when the overall learning patterns are not available in database. Therefore, three different data mining algorithm is employed with system. Proposed system consists of K-mean clustering algorithm for finding the relationship among data in order to filter data instances. The implementation of the proposed classification system is performed using MATLAB environment and performance of designed classifier is evaluated. The obtained results from the simulation demonstrate after filtering steps. On the other hand the classification accuracy is adoptable with low number of training cycles with less time and space complexity.
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Latifi, Zeinab, Kamal Jamshidi i Ali Bohlooli. "Increasing the Efficiency of IDS Systems by Hardware Implementation of Packet Capturing". International Journal of Computer Network and Information Security 5, nr 10 (1.08.2013): 30–36. http://dx.doi.org/10.5815/ijcnis.2013.10.05.
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Sammon, Cormac J., Thomas P. Leahy i Sreeram Ramagopalan. "Nonindependence of patient data in the clinical practice research datalink: a case study in atrial fibrillation patients". Journal of Comparative Effectiveness Research 9, nr 6 (kwiecień 2020): 395–403. http://dx.doi.org/10.2217/cer-2019-0191.
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Aim: The impact of different strategies to handle patients with data recorded under multiple Clinical Practice Research Datalink (CPRD) identifiers (IDs) is unknown. Patients and methods: Six approaches to handling patients appearing under multiple CPRD IDs were defined. The impact of the approaches was illustrated using a case study describing the clinical characteristics of a population of nonvalvular atrial fibrillation patients. Results: 5.6% of patients had more than one CPRD ID. Across all six approaches implemented, no material difference in the characteristics of nonvalvular atrial fibrillation patients were observed. Conclusion: While strategies which longitudinally append patient registration periods under different CPRD IDs maintain independence while using all available data, their implementation had little impact on the results of our case study.
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Bilyeu, Heather, Jon Washburn, Lacey Vermette i Tracy Klug. "Validation and Implementation of a Highly Sensitive and Efficient Newborn Screening Assay for Mucopolysaccharidosis Type II". International Journal of Neonatal Screening 6, nr 4 (14.10.2020): 79. http://dx.doi.org/10.3390/ijns6040079.
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Mucopolysaccharidosis Type II (MPS II), also known as Hunter syndrome, is a lysosomal storage disorder (LSD) caused by a deficiency of the lysosomal enzyme iduronate-2-sulfatase (IDS). MPS II satisfies all criteria defined by the Advisory Committee on Heritable Disorders in Newborns and Children (ACHDNC) for inclusion in the Recommended Uniform Screening Panel (RUSP) for newborn screening, apart from the fact that only minimal prospective population screening data are available. This report details the analytical validation, clinical validation, and implementation of a fluorometric assay for measurement of IDS activity in newborn dried blood spot (DBS) specimens at the Missouri State Public Health Laboratory (MSPHL). The assay is performed in a microwell plate format requiring approximately 15 min of hands-on time per plate and an incubation time of two hours. The analytical validation of this assay included linearity, analytical sensitivity, precision, and carry-over testing. Clinical validation was completed using more than 5000 deidentified presumptive normal newborn DBS specimens as well as seven specimens from patients known to be affected with MPS II. Following validation, MSPHL began prospective screening using the IDS assay on 1 November 2018. In the first 18 months of screening (to 30 June 2020), 146,954 specimens were prospectively screened using the method. Two newborns were identified with severe Hunter syndrome and the assay had a presumptive positive rate of 0.022%.
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Wei, Shugong. "Implementation and evaluation of a laser scan localization scheme for sensor nodes". Sensor Review 40, nr 1 (13.01.2020): 97–106. http://dx.doi.org/10.1108/sr-08-2019-0210.
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Purpose In this paper, an experimental apparatus was designed and subsequent theoretical analysis and simulations were conducted on the effectiveness and advantages of a novel laser beam scan localization (BLS) system. Design/methodology/approach The system used a moving location assistant (LA) with a laser beam, through which the deployed area was scanned. The laser beam sent identity documents (IDs) to unknown nodes to obtain the sensor locations. Findings The results showed that the system yielded significant benefits compared with other localization methods, and a high localization accuracy could be achieved without the aid of expensive hardware on the sensor nodes. Furthermore, four positioning mode features in this localization system were realized and compared. Originality/value In this paper, an experimental apparatus was designed and subsequent theoretical analysis and simulations were conducted on the effectiveness and advantages of a novel laser BLS system. The system used a moving LA with a laser beam, through which the deployed area was scanned. The laser beam sent IDs to unknown nodes to obtain the sensor locations.
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Nikoloudakis, Yannis, Ioannis Kefaloukos, Stylianos Klados, Spyros Panagiotakis, Evangelos Pallis, Charalabos Skianis i Evangelos K. Markakis. "Towards a Machine Learning Based Situational Awareness Framework for Cybersecurity: An SDN Implementation". Sensors 21, nr 14 (20.07.2021): 4939. http://dx.doi.org/10.3390/s21144939.
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The ever-increasing number of internet-connected devices, along with the continuous evolution of cyber-attacks, in terms of volume and ingenuity, has led to a widened cyber-threat landscape, rendering infrastructures prone to malicious attacks. Towards addressing systems’ vulnerabilities and alleviating the impact of these threats, this paper presents a machine learning based situational awareness framework that detects existing and newly introduced network-enabled entities, utilizing the real-time awareness feature provided by the SDN paradigm, assesses them against known vulnerabilities, and assigns them to a connectivity-appropriate network slice. The assessed entities are continuously monitored by an ML-based IDS, which is trained with an enhanced dataset. Our endeavor aims to demonstrate that a neural network, trained with heterogeneous data stemming from the operational environment (common vulnerability enumeration IDs that correlate attacks with existing vulnerabilities), can achieve more accurate prediction rates than a conventional one, thus addressing some aspects of the situational awareness paradigm. The proposed framework was evaluated within a real-life environment and the results revealed an increase of more than 4% in the overall prediction accuracy.
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Esterline, Albert, i Sridhar Kota. "A general paradigm for routine design—theory and implementation". Artificial Intelligence for Engineering Design, Analysis and Manufacturing 6, nr 2 (maj 1992): 73–93. http://dx.doi.org/10.1017/s0890060400002973.
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The concept of discretization of a design space is used to make initial selection of prior designs using specification matching, and to direct redesign with evaluation and iteration. A general paradigm for routine design has been developed and implemented in a system called IDS (Initial Design Selection.) For a given design domain, certain characteristics are identified that allow all specifications and models (which represent prior designs) in that design domain to be described in terms of their values or intervals that these values may lie in. These characteristics are seen as dimensions of a design space discretized into a finite number of partitions. Each partition is represented by a model, thought of as occupying its center. Each such model is associated with a deep model, which contains sufficient information for the modeled device, process, or system to be realized. Despite the fact that the models inhabiting the space are shallow, the paradigm comprises a relatively rich mathematical structure. This paper describes in detail a computational methodology to implement this domain-independent paradigm. The IDS paradigm presents a convenient and structured framework for acquiring and representing domain knowledge. This paper also briefly discusses an enhanced version of the system, which attempts iterative redesign directed by the particular mismatch between a specification and an otherwise promising model. To date, this methodology has been applied in a variety of design domains, including mechanism design, hydraulic component selection, assembly methods, and non-destructive testing methods.
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Slamet, Slamet, i Izzeldin Ibrahim Mohamed Abdelaziz. "An enhanced classification framework for intrusions detection system using intelligent exoplanet atmospheric retrieval algorithm". Bulletin of Electrical Engineering and Informatics 11, nr 2 (1.04.2022): 1018–25. http://dx.doi.org/10.11591/eei.v11i2.3308.
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Currently, many companies use data mining for various implementations. One form of implementation is intrusion detection system (IDS). In IDS, the main problem for nuisance network administrators in detecting attacks is false alerts. Regardless of the methods implemented by this system, eliminating false alerts is still a huge problem. To describe data traffic passing through the network, a database of the network security layer (NSL) knowledge discovery in database (KDD) dataset is used. The massive traffic of data sent over the network contains excessive and duplicated amounts of information. This causes the classifier to be biased, reduce classification accuracy, and increase false alert. To that end, we proposed a model that significantly improve the accuracy of the intrusion detection system by eliminating false alerts, whether they are false negative or false positive negative alerts. The results show that the proposed intelligent exoplanet atmospheric retrieval (INARA) algorithm has improved accuracy and is able to detect new attack types efficiently.
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Housman, Ian, Robert Chastain i Mark Finco. "An Evaluation of Forest Health Insect and Disease Survey Data and Satellite-Based Remote Sensing Forest Change Detection Methods: Case Studies in the United States". Remote Sensing 10, nr 8 (27.07.2018): 1184. http://dx.doi.org/10.3390/rs10081184.
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The Operational Remote Sensing (ORS) program leverages Landsat and MODIS data to detect forest disturbances across the conterminous United States (CONUS). The ORS program was initiated in 2014 as a collaboration between the US Department of Agriculture Forest Service Geospatial Technology and Applications Center (GTAC) and the Forest Health Assessment and Applied Sciences Team (FHAAST). The goal of the ORS program is to supplement the Insect and Disease Survey (IDS) and MODIS Real-Time Forest Disturbance (RTFD) programs with imagery-derived forest disturbance data that can be used to augment traditional IDS data. We developed three algorithms and produced ORS forest change products using both Landsat and MODIS data. These were assessed over Southern New England and the Rio Grande National Forest. Reference data were acquired using TimeSync to conduct an independent accuracy assessment of IDS, RTFD, and ORS products. Overall accuracy for all products ranged from 71.63% to 92.55% in the Southern New England study area and 63.48% to 79.13% in the Rio Grande National Forest study area. While the accuracies attained from the assessed products are somewhat low, these results are similar to comparable studies. Although many ORS products met or exceeded the overall accuracy of IDS and RTFD products, the differences were largely statistically insignificant at the 95% confidence interval. This demonstrates the current implementation of ORS is sufficient to provide data to augment IDS data.
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Purnama, Tommy, Yusuf Muhyidin i Dayan Singasatia. "IMPLEMENTASI INTRUSION DETECTION SYSTEM (IDS) SNORT SEBAGAI SISTEM KEAMANAN MENGGUNAKAN WHATSAPP DAN TELEGRAM SEBAGAI MEDIA NOTIFIKASI". JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI 14, nr 2 (1.09.2023): 358–69. http://dx.doi.org/10.51903/jtikp.v14i2.726.
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Intrusion Detection System (IDS) adalah sebuah sistem yang berfungsi untuk mengidentifikasi dan mendeteksi serangan yang dilakukan oleh pihak-pihak yang tidak sah pada sebuah jaringan. Namun, beberapa sistem IDS yang ada saat ini memiliki kekurangan dalam memberikan notifikasi kepada administrator jika terjadi serangan, terkadang administrator mungkin tidak dapat memantau jaringan setiap saat. Hal ini dapat menyebabkan serangan yang tidak terdeteksi pada jaringan dan memberikan celah bagi peretas untuk mengambil kendali atas sistem. Oleh karena itu, perlu adanya Implementasi IDS menggunakan WhatsApp dan Telegram sebagai Media Notifikasi untuk memastikan keamanan jaringan yang lebih baik dan efektif. Network Development Life Cycle (NDLC) adalah sebuah pendekatan yang digunakan untuk mengembangkan atau merancang sistem jaringan komputer. Metode ini memungkinkan pemantauan terhadap sistem yang sedang dirancang atau dikembangkan agar dapat mengetahui kinerjanya dengan lebih baik, Metode NDLC terdiri dari 6 (enam) tahapan yaitu Analysis, Design, Simulation Prototype, Implementation, Monitoring dan Management. Setelah dilakukan pengujian, disimpulkan bahwa IDS Snort dapat mengidentifikasi dan mendeteksi berbagai serangan, seperti ping attack (ICMP Traffic), Port Scanning, serta DOS/DDOS UDP Flooding yang ditujukan ke server berdasarkan rules IDS yang dibuat dan juga bash shell mampu merekam dan mengirimkan pesan alert ketika terjadi serangan melalui WhatsApp dan Telegram. Jumlah pesan alert yang terkirim berbeda tergantung pada jenis serangan, durasi serangan dan juga media notifikasi yang digunakan.
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Reddy, N. Chandra Sekhar. "An Implementation of Novel Feature Subset Selection Algorithm for IDS in Mobile Networks". International Journal of Advanced Trends in Computer Science and Engineering 8, nr 5 (15.10.2019): 2132–41. http://dx.doi.org/10.30534/ijatcse/2019/43852019.
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Puschmann, Paul, i Luciana Quaranta. "Editorial". Historical Life Course Studies 5 (11.01.2018): 1–2. http://dx.doi.org/10.51964/hlcs9333.
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Historical Life Course Studies, a journal in population studies, aims to stimulate and facilitate the implementation of IDS (Intermediate Data Structure, a standard data format for large historical databases), and to publish the results from (comparative) research with the help of large historical databases. The journal publishes not only empirical articles, but also descriptions (of the construction) of new and existing large historical databases, as well as articles dealing with database documentation, the transformation of existing databases into the IDS format, the development of algorithms and extraction software and all other issues related to the methodology of large historical databases.
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Powell, James, Carol Hoover, Andrew Gordon i Michelle Mittrach. "Bridging identity challenges: why and how one library plugged ORCiD into their enterprise". Library Hi Tech 37, nr 3 (16.09.2019): 625–39. http://dx.doi.org/10.1108/lht-04-2018-0046.
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Purpose The purpose of this paper is to describe the implementation and impact of a locally customized Open Researcher and Contributor ID (ORCiD) profile wizard. It also provides a broader context for adopting ORCiD as an identity and single sign-on solution. Design/methodology/approach A custom web application was designed by a library team and implemented using a combination of the OAuth protocol and the ORCiD web services API. The tool leveraged a rich, curated set of local publication data, and exposed integration hooks that allowed other enterprise systems to connect ORCiD IDs with an internal employee identifier. Findings Initially the tool saw only modest use. Ultimately its success depended upon integration with other enterprise systems and the requirement of an ORCiD ID for internal funding requests, rather than exclusively on the merits of the tool. Since introduction, it has been used to generate over 1,660 ORCiDs from a population of 4,000 actively publishing researchers. Practical implications Organizations that desire to track publications by many affiliated authors would likely benefit from some sort of integration with ORCiD web services. This is particularly true for organizations that have many publishing researchers and/or track publications spanning many decades. Enterprise integration is crucial to the success of such a project. Originality/value Research inputs and research products are now primarily digital objects. So having a reliable system for associating researchers with their output is a big challenge that, if solved, could increase researcher impact and enhance digital scholarship. ORCiD IDs are a potential glue for many aspects of this problem. The design and implementation of the wizard eased and quickened adoption of ORCiD Ids by local researchers due in part to the ease with which a researcher can push publication information already held by the library to their profile. Subsequent integration of researcher ORCiD IDs with local enterprise systems has enabled real-time propagation of ORCiD IDs across research proposal workflow, publication review and content discovery systems.
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Widodo, Rio, i Imam Riadi. "Intruder Detection Systems on Computer Networks Using Host Based Intrusion Detection System Techniques". Buletin Ilmiah Sarjana Teknik Elektro 3, nr 1 (13.01.2021): 21. http://dx.doi.org/10.12928/biste.v3i1.1752.
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The openness of access to information raises various problems, including maintaining the validity and integrity of data, so a network security system is needed that can deal with potential threats that can occur quickly and accurately by utilizing an IDS (intrusion detection system). One of the IDS tools that are often used is Snort which works in real-time to monitor and detect the ongoing network by providing warnings and information on potential threats in the form of DoS attacks. DoS attacks run to exhaust the packet path by requesting packets to a target in large and continuous ways which results in increased usage of CPU (central processing unit), memory, and ethernet or WiFi networks. The snort IDS implementation can help provide accurate information on network security that you want to monitor because every communication that takes place in a network, every event that occurs and potential attacks that can paralyze the internet network are monitored by snort.
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Inman, D., D. Simidchiev i P. Jeffrey. "Elicitation of expert knowledge to develop decision support tools for use in water demand management planning". Water Supply 7, nr 5-6 (1.12.2007): 53–60. http://dx.doi.org/10.2166/ws.2007.110.
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This paper examines the use of influence diagrams (IDs) in water demand management (WDM) strategy planning with the specific objective of exploring how IDs can be used in developing computer-based decision support tools (DSTs) to complement and support existing WDM decision processes. We report the results of an expert consultation carried out in collaboration with water industry specialists in Sofia, Bulgaria. The elicited information is presented as influence diagrams and the discussion looks at their usefulness in WDM strategy design and the specification of suitable modelling techniques. The paper concludes that IDs themselves are useful in developing model structures for use in evidence-based reasoning models such as Bayesian Networks, and this is in keeping with the objectives set out in the introduction of integrating DSTs into existing decision processes. The paper will be of interest to modellers, decision-makers and scientists involved in designing tools to support resource conservation strategy implementation.
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Sadikin, Fal, i Nuruddin Wiranda. "ANOMALY DETECTION IN ZIGBEE-BASED IOT USING SECURE AND EFFICIENT DATA COLLECTION". Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) 8, nr 1 (30.04.2023): 7–16. http://dx.doi.org/10.20527/jtiulm.v8i1.152.
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This article outlines various techniques for detecting types of attacks that may arise in ZigBee-based IoT system. The researchers introduced a hybrid Intrusion Detection System (IDS), combining rule-based intrusion detection and machine learning-based anomaly detection. Rule-based attack detection techniques are used to provide an accurate detection method for known attacks. However, determining accurate detection rules requires significant human effort that is susceptible to error. If it is done incorrectly, it can result in false alarms. Therefore, to alleviate this potential problem, the system is being upgraded by combining it (hybrid) with machine learning-based anomaly detection. This article expounds the researchers’ IDS implementation covering a wide variety of detection techniques to detect both known attacks and potential new types of attacks in ZigBee-based IoT system. Furthermore, a safe and efficient meth-od for large-scale IDS data collection is introduced to provide a trusted reporting mechanism that can operate on the stringent IoT resource requirements appropriate to today's IoT systems.
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Nazir, Anjum, Zulfiqar Memon, Touseef Sadiq, Hameedur Rahman i Inam Ullah Khan. "A Novel Feature-Selection Algorithm in IoT Networks for Intrusion Detection". Sensors 23, nr 19 (28.09.2023): 8153. http://dx.doi.org/10.3390/s23198153.
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The Internet of Things (IoT) and network-enabled smart devices are crucial to the digitally interconnected society of the present day. However, the increased reliance on IoT devices increases their susceptibility to malicious activities within network traffic, posing significant challenges to cybersecurity. As a result, both system administrators and end users are negatively affected by these malevolent behaviours. Intrusion-detection systems (IDSs) are commonly deployed as a cyber attack defence mechanism to mitigate such risks. IDS plays a crucial role in identifying and preventing cyber hazards within IoT networks. However, the development of an efficient and rapid IDS system for the detection of cyber attacks remains a challenging area of research. Moreover, IDS datasets contain multiple features, so the implementation of feature selection (FS) is required to design an effective and timely IDS. The FS procedure seeks to eliminate irrelevant and redundant features from large IDS datasets, thereby improving the intrusion-detection system’s overall performance. In this paper, we propose a hybrid wrapper-based feature-selection algorithm that is based on the concepts of the Cellular Automata (CA) engine and Tabu Search (TS)-based aspiration criteria. We used a Random Forest (RF) ensemble learning classifier to evaluate the fitness of the selected features. The proposed algorithm, CAT-S, was tested on the TON_IoT dataset. The simulation results demonstrate that the proposed algorithm, CAT-S, enhances classification accuracy while simultaneously reducing the number of features and the false positive rate.
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Matthijs, Koen, i Paul Puschmann. "Editorial". Historical Life Course Studies 2 (11.05.2015): 37. http://dx.doi.org/10.51964/hlcs9357.
Pełny tekst źródłaStreszczenie:
Historical Life Course Studies, a journal in population studies, aims to stimulate and facilitate the implementation of IDS (Intermediate Data Structure, a standard data format for large historical databases), and to publish the results from (comparative) research with the help of large historical databases. The journal publishes not only empirical articles, but also descriptions (of the construction) of new and existing large historical databases, as well as articles dealing with database documentation, the transformation of existing databases into the IDS format, the development of algorithms and extraction software and all other issues related to the methodology of large historical databases.
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Dulanovic, Nenad, Dane Hinic i Dejan Simic. "An intrusion prevention system as a proactive security mechanism in network infrastructure". Yugoslav Journal of Operations Research 18, nr 1 (2008): 109–22. http://dx.doi.org/10.2298/yjor0801109d.
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A properly configured firewall is a good starting point in securing a computer network. However, complex network environments that involve higher number of participants and endpoints require better security infrastructure. Intrusion Detection Systems (IDS), proposed as a solution to perimeter defense, have many open problems and it is clear that better solutions must be found. Due to many unsolved problems associated with IDS, Intrusion Prevention Systems (IPS) are introduced. The main idea in IPS is to be proactive. This paper gives an insight of Cobrador Bouncer IPS implementation. System architecture is given and three different Bouncer IPS deployment modes are presented. The Bouncer IPS as a proactive honeypot is also discussed.
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Hulsen, Tim. "BioVenn – an R and Python package for the comparison and visualization of biological lists using area-proportional Venn diagrams". Data Science 4, nr 1 (21.05.2021): 51–61. http://dx.doi.org/10.3233/ds-210032.
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One of the most popular methods to visualize the overlap and differences between data sets is the Venn diagram. Venn diagrams are especially useful when they are ‘area-proportional’ i.e. the sizes of the circles and the overlaps correspond to the sizes of the data sets. In 2007, the BioVenn web interface was launched, which is being used by many researchers. However, this web implementation requires users to copy and paste (or upload) lists of IDs into the web browser, which is not always convenient and makes it difficult for researchers to create Venn diagrams ‘in batch’, or to automatically update the diagram when the source data changes. This is only possible by using software such as R or Python. This paper describes the BioVenn R and Python packages, which are very easy-to-use packages that can generate accurate area-proportional Venn diagrams of two or three circles directly from lists of (biological) IDs. The only required input is two or three lists of IDs. Optional parameters include the main title, the subtitle, the printing of absolute numbers or percentages within the diagram, colors and fonts. The function can show the diagram on the screen, or it can export the diagram in one of the supported file formats. The function also returns all thirteen lists. The BioVenn R package and Python package were created for biological IDs, but they can be used for other IDs as well. Finally, BioVenn can map Affymetrix and EntrezGene to Ensembl IDs. The BioVenn R package is available in the CRAN repository, and can be installed by running ‘install.packages(“BioVenn”)’. The BioVenn Python package is available in the PyPI repository, and can be installed by running ‘pip install BioVenn’. The BioVenn web interface remains available at https://www.biovenn.nl.
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Sadikin, Fal, i Nuruddin Wiranda. "INTRUSION DETECTION SYSTEM FOR ZIGBEE-BASED IOT USING DATA ANALYSIS RULES". Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) 8, nr 1 (30.04.2023): 23–30. http://dx.doi.org/10.20527/jtiulm.v8i1.153.
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The market for Internet of Things (IoT) products and services has grown rapidly. It has been predicted that the deployment of these IoT applications will grow exponentially in the near future. However, the rapid growth of IoT brings new security risks and potentially opens new types of attacks for systems and networks. This article outlines various techniques for detecting known attacks in ZigBee-based IoT systems. We introduced an Detection System (IDS) specific for ZigBee using data analytics method, that are used to provide an accurate detection method for known attacks. This article looks at our IDS implementation covering a wide variety of detection techniques to detect known attacks ZigBee IoT systems.
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Huh, Jun-Ho. "Implementation of lightweight intrusion detection model for security of smart green house and vertical farm". International Journal of Distributed Sensor Networks 14, nr 4 (kwiecień 2018): 155014771876763. http://dx.doi.org/10.1177/1550147718767630.
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With the current global food production capability, it is not difficult to anticipate that there will be a global food shortage when the world population grows beyond 10 billion by the end of the 21st century. Many projects are in motion to deal with this problem and some of them are considered to be quite feasible. Development and implementation of smart green houses and vertical farms are two major solutions for the expected crisis, but as other ICT-based systems, their security problems must be dealt with. Nevertheless, current network forensics is still unable to fully monitor and analyze computer network traffic to gather the evidences of malicious attacks or intrusions. Although major companies and government agencies have introduced various types of high-speed IDS into their networks, smaller firms or private organizations are unable to do so because of the cost involved. The lightweight IDS proposed in this study can be a suitable solution as this system can be operated with a common PC and peripherals. This system also underwent a test bed experiment and proved its efficiency. Jpcap library was used to capture transport packets which were then classified using typical communications protocols. The packet headers were subjected to analysis and the results were stored in database for later applications.
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Hindy, Hanan, Robert Atkinson, Christos Tachtatzis, Jean-Noël Colin, Ethan Bayne i Xavier Bellekens. "Utilising Deep Learning Techniques for Effective Zero-Day Attack Detection". Electronics 9, nr 10 (14.10.2020): 1684. http://dx.doi.org/10.3390/electronics9101684.
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Machine Learning (ML) and Deep Learning (DL) have been used for building Intrusion Detection Systems (IDS). The increase in both the number and sheer variety of new cyber-attacks poses a tremendous challenge for IDS solutions that rely on a database of historical attack signatures. Therefore, the industrial pull for robust IDSs that are capable of flagging zero-day attacks is growing. Current outlier-based zero-day detection research suffers from high false-negative rates, thus limiting their practical use and performance. This paper proposes an autoencoder implementation for detecting zero-day attacks. The aim is to build an IDS model with high recall while keeping the miss rate (false-negatives) to an acceptable minimum. Two well-known IDS datasets are used for evaluation—CICIDS2017 and NSL-KDD. In order to demonstrate the efficacy of our model, we compare its results against a One-Class Support Vector Machine (SVM). The manuscript highlights the performance of a One-Class SVM when zero-day attacks are distinctive from normal behaviour. The proposed model benefits greatly from autoencoders encoding-decoding capabilities. The results show that autoencoders are well-suited at detecting complex zero-day attacks. The results demonstrate a zero-day detection accuracy of 89–99% for the NSL-KDD dataset and 75–98% for the CICIDS2017 dataset. Finally, the paper outlines the observed trade-off between recall and fallout.
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Chalichalamala, Silpa, Niranjana Govindan i Ramani Kasarapu. "Logistic Regression Ensemble Classifier for Intrusion Detection System in Internet of Things". Sensors 23, nr 23 (3.12.2023): 9583. http://dx.doi.org/10.3390/s23239583.
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The Internet of Things (IoT) is a powerful technology that connect its users worldwide with everyday objects without any human interference. On the contrary, the utilization of IoT infrastructure in different fields such as smart homes, healthcare and transportation also raises potential risks of attacks and anomalies caused through node security breaches. Therefore, an Intrusion Detection System (IDS) must be developed to largely scale up the security of IoT technologies. This paper proposes a Logistic Regression based Ensemble Classifier (LREC) for effective IDS implementation. The LREC combines AdaBoost and Random Forest (RF) to develop an effective classifier using the iterative ensemble approach. The issue of data imbalance is avoided by using the adaptive synthetic sampling (ADASYN) approach. Further, inappropriate features are eliminated using recursive feature elimination (RFE). There are two different datasets, namely BoT-IoT and TON-IoT, for analyzing the proposed RFE-LREC method. The RFE-LREC is analyzed on the basis of accuracy, recall, precision, F1-score, false alarm rate (FAR), receiver operating characteristic (ROC) curve, true negative rate (TNR) and Matthews correlation coefficient (MCC). The existing researches, namely NetFlow-based feature set, TL-IDS and LSTM, are used to compare with the RFE-LREC. The classification accuracy of RFE-LREC for the BoT-IoT dataset is 99.99%, which is higher when compared to those of TL-IDS and LSTM.
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Alamsyah, Nur. "ENHANCING INTRUSION DETECTION SYSTEM ON NODEMCU WITH ENSEMBLE VOTING". Jurnal Elektro dan Telekomunikasi Terapan 9, nr 2 (6.03.2023): 1271. http://dx.doi.org/10.25124/jett.v9i2.5437.
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As part of the Internet, a NodeMCU becomes a vulnerability to cyber-attack, so the intrusion detection system (IDS) against cyber-attack on the NodeMCU becomes a poignant research challenge. Several studies have applied several machine learning techniques for IDS on NodeMCU; however, there is a research opportunity to improve the performance of existing models. This research aims to increase the IDS performance on NodeMCU with ensemble voting. We hypothesize the realization of how the implementation of an IDS in NodeMCU. Then we obtain and observe a dataset from Kaggle. The dataset comprises five attacks: misconfiguration, DDoS, probe, scanning, and MiTM. Then we design the detection with ensemble voting consisting of a decision tree and a random forest. We benchmark our proposed solution with decision trees and random forest performance. This study uses several test metrics, including , , , and .The test results show that the decision tree has better Precision in predicting misconfiguration attacks and scan attacks than random forests. On the other hand, the random forest has better in predicting normal data, DDoS attacks, probe attacks, and MiTM attacks. In terms of , ensemble voting has the best performance, which is , compared to the decision tree and random forest, which are and , respectively. We conclude that by assembling a decision tree in the random forest with ensemble voting, random forest performance can improve.
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Berenice Arzate-Rueda, Enrique Reyes-Archundia, Juan C. Olivares-Rojas, Jose A. Gutiérrez-Gnecchi, Maria del C. García-Ramírez, Marco V. Chávez-Báez i Javier A. Rodríguez-Herrejón. "Intrusion detection system in a hardware in the loop scenario". Global Journal of Engineering and Technology Advances 17, nr 3 (30.12.2023): 036–44. http://dx.doi.org/10.30574/gjeta.2023.17.3.0247.
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Detecting perturbation in electrical signals is crucial to assure power quality (PQ) and protect equipment connected to an electrical network. Some of the information generated by disturbances analysis can be communicated using Internet of Things (IoT) protocols, but it is vital to verify the integrity of the data. As a result of the lack of security presented by IoT devices, the proposal of this work is based on the implementation of an algorithm based on IDS that allows identifying attacks or failures in the security of an IoT-based PQ disturbance detection system implemented in a BeagleBone Black Wireless. The Sparta and Sqlmap programs were used as tools to perform tests and detect security flaws in the BeagleBone, verifying essential operations of the IDS.
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Konyeha, Susan, i Emmanuel A. Onibere. "Computer Immunity Using an Intrusion Detection System (IDS)". Advanced Materials Research 824 (wrzesień 2013): 200–205. http://dx.doi.org/10.4028/www.scientific.net/amr.824.200.
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Computers are involved in every aspect of modern society and have become an essential part of our lives, but their vulnerability is of increasing concern to us. Security flaws are inherent in the operation of computers Most flaws are caused by errors in the process of software engineering or unforeseen mishaps and it is difficult to solve these problems by conventional methods. A radical way of constantly monitoring the system for newly disclosed vulnerabilities is required. In order to devise such a system, this work draws an analogy between computer immune systems and the human immune system. The computer immune system is the equivalent of the human immune system. The primary objective of this paper is to use an intrusion detection system in the design and implementation of a computer immune system that would be built on the framework of the human immune system. This objective is successfully realized and in addition a prevention mechanism using the windows IP Firewall feature has been incorporated. Hence the system is able to perform intrusion detection and prevention. Data was collected about events occurring in a computer network that violate predefined security policy, such as attempts to affect the confidentiality, integrity or its availability using Snort rules for known attacks and adaptive detection for the unknown attacks. The system was tested using real-time data and Intrusion Detection evaluation (IDEVAL) Department of Defense Advanced Research Projects Agency (DARPA) data set. The results were quite encouraging as few false positive were recorded.
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Pinuji, Sukmo. "INTEGRASI SISTEM INFORMASI PERTANAHAN DAN INFRASTRUKTUR DATA SPASIAL DALAM RANGKA PERWUJUDAN ONE MAP POLICY". BHUMI: Jurnal Agraria dan Pertanahan 2, nr 1 (31.05.2016): 48. http://dx.doi.org/10.31292/jb.v2i1.31.
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Abstract: Land information has important roles in Spatial Data Infrastructure (SDI), as it contains information of land use,utilization, even land value. Land information also has specific characteristic: dynamics and has sensitivity related to the needs ofdifferent parties. Moreover, the “new paradigm of Land Information System (LIS)” should be able to promote spatial based decisionmaking for sustainable development, thus demand the integration of LIS to National SDI (NSDI), to facilitate spatial data accesswithin stakeholders. Nonetheless, this condition has not been met. This research identified and analyzed some “critical points” ofthe integration of LIS to NSDI, based on six elements of SDI, through the implementation of Geo-KKP, a milestone of theimplementation of SDI in the organization of Ministry of Agrarian and Land Use Planning/NLA. The results show that Geo-KKP isdeveloped mainly to support land registration, and has not been developed to support NSDI. Furthermore, the integration of LISto support NSDI can be effectively achieved through the comprehensive development of the six elements of SDI.Key words: LIS, IDS, Geo-KKPIntisari: Informasi pertanahan memiliki peran penting dalam Infrastruktur Data Spasial (IDS), karena menyediakan informasimengenai pemilikan, pemanfaatan sampai informasi nilai tanah. Selain itu, perkembangan “paradigma baru” bahwa Sistem InformasiPertanahan (SIP) harus berperan dalam spatial based decision making untuk terwujudnya sustainable development menjadikantantangan tersendiri dalam menciptakan sistem yang terintegrasi ke dalam Infrastruktur Data Spasial Nasional (IDSN), agar informasispasial dapat dengan mudah diakses oleh pihak-pihak yang berkepentingan. Dalam implementasinya, SIP belum dapat secaraoptimal terintegrasi dalam IDSN. Penelitian ini mengidentifikasi dan menganalisis berbagai “titik sensitif” dalam pengintegrasianSIP ke dalam IDSN, berdasarkan enam elemen IDS, melalui implementasi Geo-KKP, yang merupakan rintisan IDS di level organisasiKementerian ATR/BPN. Hasil penelitian menunjukkan bahwa Geo-KKP masih dikembangkan secara parsial dari konsep IDSN,sebatas untuk mendukung kegiatan pendaftaran tanah, dan belum mencakup kepentingan yang lebih luas sebagaimana yang diinginkanoleh konsep IDS.Untuk dapat mengembangkan SIP yang dapat memenuhi tuntutan tersebut, keenam elemen IDS tersebut harusdiafiliasi secara komprehensif dan menyeluruh, dan tidak secara parsial.Kata kunci: SIP, IDS, Geo-KKP
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MacIntosh, Eric, A. Lauren Couture i Kirsty Spence. "Management challenges in delivering an international sport and development program". Sport, Business and Management: An International Journal 5, nr 3 (13.07.2015): 276–96. http://dx.doi.org/10.1108/sbm-07-2012-0028.
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Purpose – The primary purpose of this paper is to explore stakeholder perceptions of an international sport for development program so as to identify some of the management challenges within a strategic management framework. The secondary purpose is to provide recommendations for the focal organization’s leadership based on those stakeholder perceptions. Hence, participants in this study directly experienced the facilitation and implementation of the international sport for development program. Participant viewpoints are expressed in efforts to identify improvement opportunities in the delivery and operations of this sport for development program. Design/methodology/approach – In this qualitative research, a case study design was chosen to produce a detailed account of the Commonwealth Games Association of Canada’s (CGC) International Sport and Development (IDS) program. Interviews were conducted with 24 alumni of the IDS program, five CGC IDS administrators, and ten host IDS organization administrators from African and Caribbean regions. Findings – Findings demonstrated shared perspectives regarding the challenges and various management practices among the three stakeholder groups investigated. In particular, funding and human resource stress was found to be the largest obstacles of maintaining programming and achieving desired outcomes. Several strengths and limitations in the program design, monitoring and evaluation strategy, and program documentation of outcomes were found which can presumably be used to help formulate management strategy moving forward in efforts for continuous improvement. Research limitations/implications – The study does not take into account the stakeholder group of participants whom were deemed to be on the receiving end of the program and not responsible for the delivery and operations of the initiatives which were the focus of the study. Practical implications – Recommendations in lieu of present challenges and objectives are also offered and are based on information from the facilitators and implementers of the principal program of research and the results of the semi-structured interviews. Originality/value – This study examines three different stakeholders that are responsible for the facilitation and implementation of the design, delivery, and daily operations of sport for development projects within an international partnership context.
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Ghori, Muhammad Rizwan, Tat-Chee Wan i Gian Chand Sodhy. "Bluetooth Low Energy Mesh Networks: Survey of Communication and Security Protocols". Sensors 20, nr 12 (25.06.2020): 3590. http://dx.doi.org/10.3390/s20123590.
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Bluetooth Low Energy (BLE) Mesh Networks enable flexible and reliable communications for low-power Internet of Things (IoT) devices. Most BLE-based mesh protocols are implemented as overlays on top of the standard Bluetooth star topologies while using piconets and scatternets. Nonetheless, mesh topology support has increased the vulnerability of BLE to security threats, since a larger number of devices can participate in a BLE Mesh network. To address these concerns, BLE version 5 enhanced existing BLE security features to deal with various authenticity, integrity, and confidentiality issues. However, there is still a lack of detailed studies related to these new security features. This survey examines the most recent BLE-based mesh network protocols and related security issues. In the first part, the latest BLE-based mesh communication protocols are discussed. The analysis shows that the implementation of BLE pure mesh protocols remains an open research issue. Moreover, there is a lack of auto-configuration mechanisms in order to support bootstrapping of BLE pure mesh networks. In the second part, recent BLE-related security issues and vulnerabilities are highlighted. Strong Intrusion Detection Systems (IDS) are essential for detecting security breaches in order to protect against zero-day exploits. Nonetheless, viable IDS solutions for BLE Mesh networks remain a nascent research area. Consequently, a comparative survey of IDS approaches for related low-power wireless protocols was used to map out potential approaches for enhancing IDS solutions for BLE Mesh networks.