Journal articles: 'Metric Security'

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Neto, Afonso Araújo, and Marco Vieira. "Benchmarking Untrustworthiness." International Journal of Dependable and Trustworthy Information Systems 1, no. 2 (April 2010): 32–54. http://dx.doi.org/10.4018/jdtis.2010040102.

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Benchmarking security is hard and, although there are many proposals of security metrics in the literature, no consensual quantitative security metric has been previously proposed. A key difficulty is that security is usually more influenced by what is unknown about a system than by what is known. In this paper, the authors propose the use of an untrustworthiness metric for benchmarking security. This metric, based on the idea of quantifying and exposing the trustworthiness relationship between a system and its owner, represents a powerful alternative to traditional security metrics. As an example, the authors propose a benchmark for Database Management Systems (DBMS) that can be easily used to assess and compare alternative database configurations based on minimum untrustworthiness, which is a low-cost and high-reward trust-based metric. The practical application of the benchmark in four real large database installations shows that untrustworthiness is a powerful metric for administrators to make informed security decisions by taking into account the specifics needs and characteristics of the environment being managed.

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Shan, Chun, Benfu Jiang, Jingfeng Xue, Fang Guan, and Na Xiao. "An Approach for Internal Network Security Metric Based on Attack Probability." Security and Communication Networks 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/3652170.

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A network security metric may provide quantifiable evidence to assist security practitioners in securing computer networks. However, research on security metrics based on attack graph is not applicable to the characteristics of internal attack; therefore we propose an internal network security metric method based on attack probability. Our approach has the following benefits: it provides the method of attack graph simplification with monitoring event node which could solve the attack graph exponential growth with the network size, while undermining the disguise of internal attacks and improving the efficiency of the entire method; the method of attack probability calculation based on simplified attack graph can simplify the complexity of internal attacks and improve the accuracy of the approach.

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Díaz, Álvaro, Javier González-Bayon, and Pablo Sánchez. "Security Estimation in Wireless Sensor Network Simulator." Journal of Circuits, Systems and Computers 25, no. 07 (April 22, 2016): 1650067. http://dx.doi.org/10.1142/s0218126616500675.

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Sensor nodes are low-power and low-cost devices with the requirement of a long autonomous lifetime. Therefore, the nodes have to use the available power carefully and avoid expensive computations or radio transmissions. In addition, as some wireless sensor networks (WSNs) process sensitive data, selecting a security protocol is vital. Cryptographic methods used in WSNs should fulfill the constraints of sensor nodes and should be evaluated for their security and power consumption. WSN engineers use several metrics to obtain estimations prior to network deployment. These metrics are usually related to power and execution time estimation. However, security is a feature that cannot be estimated and it is either “active” or “inactive”, with no possibility of introducing intermediate security levels. This lack of flexibility is a disadvantage in real deployments where different operation modes with different security and power specifications are often needed. This paper proposes including a new security estimation metric in a previously proposed framework for WSN simulation and embedded software (SW) performance analysis. This metric is called Security Estimation Metric (SEM) and it provides information about the security encryption used in WSN transmissions. Results show that the metric improves flexibility, granularity and execution time compared to other cryptographic tests.

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Yee, George O. M. "Designing Sound Security Metrics." International Journal of Systems and Software Security and Protection 10, no. 1 (January 2019): 1–21. http://dx.doi.org/10.4018/ijsssp.2019010101.

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This article begins with an introduction to security metrics, describing the need for security metrics, followed by a discussion of the nature of security metrics, including the challenges found with some security metrics used in the past. The article then discusses what makes a sound security metric and proposes a rigorous step-by-step method that can be applied to design sound security metrics, and to test existing security metrics to see if they are sound metrics. This is followed by a discussion of the feasibility of having scientifically-based security metrics and whether or not such metrics are sound. Application examples are included to illustrate the design and testing of sound security metrics.

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Shao, Yanli, Jingru Zhao, Xingqi Wang, Weiwei Wu, and Jinglong Fang. "Research on Cross-Company Defect Prediction Method to Improve Software Security." Security and Communication Networks 2021 (August 24, 2021): 1–19. http://dx.doi.org/10.1155/2021/5558561.

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As the scale and complexity of software increase, software security issues have become the focus of society. Software defect prediction (SDP) is an important means to assist developers in discovering and repairing potential defects that may endanger software security in advance and improving software security and reliability. Currently, cross-project defect prediction (CPDP) and cross-company defect prediction (CCDP) are widely studied to improve the defect prediction performance, but there are still problems such as inconsistent metrics and large differences in data distribution between source and target projects. Therefore, a new CCDP method based on metric matching and sample weight setting is proposed in this study. First, a clustering-based metric matching method is proposed. The multigranularity metric feature vector is extracted to unify the metric dimension while maximally retaining the information contained in the metrics. Then use metric clustering to eliminate metric redundancy and extract representative metrics through principal component analysis (PCA) to support one-to-one metric matching. This strategy not only solves the metric inconsistent and redundancy problem but also transforms the cross-company heterogeneous defect prediction problem into a homogeneous problem. Second, a sample weight setting method is proposed to transform the source data distribution. Wherein the statistical source sample frequency information is set as an impact factor to increase the weight of source samples that are more similar to the target samples, which improves the data distribution similarity between the source and target projects, thereby building a more accurate prediction model. Finally, after the above two-step processing, some classical machine learning methods are applied to build the prediction model, and 12 project datasets in NASA and PROMISE are used for performance comparison. Experimental results prove that the proposed method has superior prediction performance over other mainstream CCDP methods.

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Tjirare, D., and F. Bhunu Shava. "Developing Security Metrics to Evaluate Employee Awareness: a Case of a Ministry in Namibia." Namibian Journal for Research, Science and Technology 1, no. 1 (October 16, 2020): 11–18. http://dx.doi.org/10.54421/njrst.v1i1.5.

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Employees that lack security awareness may cause a threat to an organisation unintentionally. A mixed research method was used to conduct a case study to evaluate the security awareness levels of employees in one ministry to reduce the risk associated with security threats.A survey using a questionnaire was carried out with the ministry employees from four different departments. Collected data was quantitatively analysed to gauge the security risk of the organisation. Analysed survey results were used todevelop security metrics using the Goal Question Metric approach and security objectives as measurements. The metric evaluated the security awareness level of employees at the ministry. Employees’ responses were validated using helpdesk statistics on incident reporting and antivirus statistics. The security metrics aim to assist the Information Technology department to detect security breaches early, and then develop a security awareness program and policies to promote security best practices. On the other hand the metrics can be used to encourage top management to get involved. The results show that employees’ awareness level was mostly low or elevated. Security standards and best practices are recommended based on the findings of risk rating per securitycategory.

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Jouini, Mouna, and Latifa Ben Arfa Rabai. "A Security Risk Management Metric for Cloud Computing Systems." International Journal of Organizational and Collective Intelligence 4, no. 3 (July 2014): 1–21. http://dx.doi.org/10.4018/ijoci.2014070101.

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Cloud computing is a growing technology used by several organizations because it presents a cost effective policy to manage and control Information Technology (IT). It delivers computing services as a public utility rather than a personal one. However, despite these benefits, it presents many challenges including access control and security problems. In order to assess security risks, the paper gives an overview of security risk management metrics. Then, it illustrates the use of a cyber security measure to describe an economic security model for cloud computing system. Moreover, it proposes a cloud provider business model for security issues. Finally, the paper shows a solution related to the vulnerabilities in cloud systems using a new quantitative metric to reduce the probability that an architectural components fails. The main aim of this article is to quantify security threats in cloud computing environments due to security breaches using a new security metric.

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Le, Ngoc Thuy, and Doan B. Hoang. "A Threat Computation Model using a Markov Chain and Common Vulnerability Scoring System and its Application to Cloud Security." Journal of Telecommunications and the Digital Economy 7, no. 1 (March 30, 2019): 37–56. http://dx.doi.org/10.18080/jtde.v7n1.181.

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Securing cyber infrastructures has become critical because they are increasingly exposed to attackers while accommodating a huge number of IoT devices and supporting numerous sophisticated emerging applications. Security metrics are essential for assessing the security risks and making effective decisions concerning system security. Many security metrics rely on mathematical models, but are mainly based on empirical data, qualitative methods, or compliance checking, and this renders the outcome far from satisfactory. Computing the probability of an attack, or more precisely a threat that materialises into an attack, forms an essential basis for a quantitative security metric. This paper proposes a novel approach to compute the probability distribution of cloud security threats based on a Markov chain and Common Vulnerability Scoring System. Moreover, the paper introduces the method to estimate the probability of security attacks. The use of the new security threat model and its computation is demonstrated through their application to estimating the probabilities of cloud threats and types of attacks.

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Kim, Kisoo, Sangho Lee, Yeowung Yun, Jaemin Choi, and Hyungjin Mun. "Security Evaluation Metric of Windows-Based Information Security Products." Indian Journal of Science and Technology 8, S8 (April 1, 2015): 10. http://dx.doi.org/10.17485/ijst/2015/v8is8/71501.

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Ito, Kosuke, Shuji Morisaki, and Atsuhiro Goto. "IoT Security-Quality-Metrics Method and Its Conformity with Emerging Guidelines." IoT 2, no. 4 (December 15, 2021): 761–85. http://dx.doi.org/10.3390/iot2040038.

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This study proposes a security-quality-metrics method tailored for the Internet of things (IoT) and evaluates conformity of the proposed approach with pertinent cybersecurity regulations and guidelines for IoT. Cybersecurity incidents involving IoT devices have recently come to light; consequently, IoT security correspondence has become a necessity. The ISO 25000 series is used for software; however, the concept of security as a quality factor has not been applied to IoT devices. Because software vulnerabilities were not the device vendors’ responsibility as product liability, most vendors did not consider the security capability of IoT devices as part of their quality control. Furthermore, an appropriate IoT security-quality metric for vendors does not exist; instead, vendors have to set their security standards, which lack consistency and are difficult to justify by themselves. To address this problem, the authors propose a universal method for specifying IoT security-quality metrics on a globally accepted scale, inspired by the goal/question/metric (GQM) method. The method enables vendors to verify their products to conform to the requirements of existing baselines and certification programs and to help vendors to tailor their quality requirements to meet the given security requirements. The IoT users would also be able to use these metrics to verify the security quality of IoT devices.

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Ali, Shahbaz, Muhammad Khalid Mahmood, Fairouz Tchier, and F. M. O. Tawfiq. "Classification of Upper Bound Sequences of Local Fractional Metric Dimension of Rotationally Symmetric Hexagonal Planar Networks." Journal of Mathematics 2021 (February 27, 2021): 1–24. http://dx.doi.org/10.1155/2021/6613033.

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The term metric or distance of a graph plays a vital role in the study to check the structural properties of the networks such as complexity, modularity, centrality, accessibility, connectivity, robustness, clustering, and vulnerability. In particular, various metrics or distance-based dimensions of different kinds of networks are used to resolve the problems in different strata such as in security to find a suitable place for fixing sensors for security purposes. In the field of computer science, metric dimensions are most useful in aspects such as image processing, navigation, pattern recognition, and integer programming problem. Also, metric dimensions play a vital role in the field of chemical engineering, for example, the problem of drug discovery and the formation of different chemical compounds are resolved by means of some suitable metric dimension algorithm. In this paper, we take rotationally symmetric and hexagonal planar networks with all possible faces. We find the sequences of the local fractional metric dimensions of proposed rotationally symmetric and planar networks. Also, we discuss the boundedness of sequences of local fractional metric dimensions. Moreover, we summarize the sequences of local fractional metric dimension by means of their graphs.

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Delli Priscoli, Francesco, Vincenzo Suraci, Roberto Germanà, Alessandro Giuseppi, Andrea Tortorelli, and Andrea Fiaschetti. "A security metric for assessing the security level of critical infrastructures." International Journal of Critical Computer-Based Systems 10, no. 1 (2020): 74. http://dx.doi.org/10.1504/ijccbs.2020.10030622.

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Tortorelli, Andrea, Andrea Fiaschetti, Alessandro Giuseppi, Vincenzo Suraci, Roberto Germanà, and Francesco Delli Priscoli. "A security metric for assessing the security level of critical infrastructures." International Journal of Critical Computer-Based Systems 10, no. 1 (2020): 74. http://dx.doi.org/10.1504/ijccbs.2020.108685.

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Khan, Naveed, Jianbiao Zhang, and Saeed Ullah Jan. "A Robust and Privacy-Preserving Anonymous User Authentication Scheme for Public Cloud Server." Security and Communication Networks 2022 (March 14, 2022): 1–14. http://dx.doi.org/10.1155/2022/1943426.

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Everyone desires to avail online services provided by different service providers securely, efficiently, and effectively. In this regard, security is still a significant concern for them. However, no one guarantees secure communication by browsing different applications remotely. To ensure confidentiality, authorization, availability, nonrepudiation, and removing eavesdropping, without a robust authentication scheme, nothing will go right. Therefore, we attempted to design a robust and privacy-preserving authentication scheme for end-users to securely access public cloud servers’ services remotely without losing performance. Our proposed scheme security has been evaluated formally using the random oracle model (ROM) and ProVerif2.03 and informally using proposition and discussion. At the same time, the performance metric has been analyzed by considering the scheme’s computation and communication costs. Upon comparing the proposed scenario with state-of-the-artwork, it has been demonstrated that the scheme is much better in terms of security and performance, as these are contradicting metrics, and the change in one conversely affects the other.

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Shi, Fan, Shaofeng Kai, Jinghua Zheng, and Yao Zhong. "XLNet-Based Prediction Model for CVSS Metric Values." Applied Sciences 12, no. 18 (September 7, 2022): 8983. http://dx.doi.org/10.3390/app12188983.

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A plethora of software vulnerabilities are exposed daily, posing a severe threat to the Internet. It is almost impossible for security experts or software developers to deal with all vulnerabilities. Therefore, it is imperative to rapidly assess the severity of the vulnerability to be able to select which one should be given preferential attention. CVSS is now the industry’s de facto evaluation standard, which is calculated with a quantitative formula to measure the severity of a vulnerability. The CVSS formula consists of several metrics related to the vulnerability’s features. Security experts need to determine the values of each metric, which is tedious and time-consuming, therefore hindering the efficiency of severity assessment. To address this problem, in this paper, we propose a method based on a pre-trained model for the prediction of CVSS metric values. More specifically, this method utilizes the XLNet model that is fine-tuned with a self-built corpus to predict the metric values from the vulnerability description text, thus reducing the burden of the assessment procedure. To verify the performance of our method, we compare the XLNet model with other pre-trained models and conventional machine learning techniques. The experimental results show that the method outperforms these models on evaluation metrics, reaching state-of-the-art performance levels.

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Adamski, Marcin, Krzysztof Kurowski, Marek Mika, Wojciech Piątek, and Jan Węglarz. "Security Aspects in Resource Management Systems in Distributed Computing Environments." Foundations of Computing and Decision Sciences 42, no. 4 (December 20, 2017): 299–313. http://dx.doi.org/10.1515/fcds-2017-0015.

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Abstract In many distributed computing systems, aspects related to security are getting more and more relevant. Security is ubiquitous and could not be treated as a separated problem or a challenge. In our opinion it should be considered in the context of resource management in distributed computing environments like Grids and Clouds, e.g. scheduled computations can be much delayed because of cyber-attacks, inefficient infrastructure or users valuable and sensitive data can be stolen even in the process of correct computation. To prevent such cases there is a need to introduce new evaluation metrics for resource management that will represent the level of security of computing resources and more broadly distributed computing infrastructures. In our approach, we have introduced a new metric called reputation, which simply determines the level of reliability of computing resources from the security perspective and could be taken into account during scheduling procedures. The new reputation metric is based on various relevant parameters regarding cyber-attacks (also energy attacks), administrative activities such as security updates, bug fixes and security patches. Moreover, we have conducted various computational experiments within the Grid Scheduling Simulator environment (GSSIM) inspired by real application scenarios. Finally, our experimental studies of new resource management approaches taking into account critical security aspects are also discussed in this paper.

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Wang, Zibo, Yaofang Zhang, Zhiyao Liu, Tongtong Li, Yilu Chen, Chen Yang, Bailing Wang, and Zhusong Liu. "A Prioritizing Interdiction Surface-Based Vulnerability Remediation Composite Metric for Industrial Control Systems." Wireless Communications and Mobile Computing 2022 (May 29, 2022): 1–16. http://dx.doi.org/10.1155/2022/6442778.

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Recently, industrial control system (ICS) has gradually been a primary attack target. The main reason is that increasing vulnerabilities exposed provide opportunities for launching multistep and multihost attacks to breach security policies. To that end, vulnerability remediations are crucial for the ICS. However, there exist three problems to be tackled in a sound way. First of all, it is impractical to remove all vulnerabilities for preventing the multistep and multihost attacks in the consideration of the actual ICS demands. Secondly, ranking vulnerability remediations lacks a guidance. The last problem is that there is a lack of a metric for qualifying the security level after each remediation. In this paper, an ICS-oriented assessment methodology is proposed for the vulnerability remediations. It consists of three phases corresponding to the above problems, including (1) prioritizing Interdiction Surfaces, (2) ranking vulnerability remediations, and (3) calculating composite metrics. The Interdiction Surface describes a minimum set of vulnerabilities of which the complete removal may interdict all discovered attack paths in the system. Particularly, it innovates to take the urgent security demands of the ICS into account. Subsequently, ranking the vulnerability in the optimal Interdiction Surface is conducive to guide the remediations with the priority. A composite metric is ultimately given to assess the security level after vulnerability remediations. The effectiveness of the proposed methodology is validated in an ICS scenario which is similar to the real-world practice. Results show that the entire procedure is suitable for the context of the ICS. Simultaneously, the composite metric enhances both the comprehensiveness and the compatibility in contrast with attack path-based metrics. Hence, it overcomes the shortcomings when they are used in isolation.

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Farid, Farnaz, Seyed Shahrestani, and Chun Ruan. "A Metric-Based Approach for Quality Evaluation in Distributed Networking Systems." International Journal of Interactive Communication Systems and Technologies 9, no. 1 (January 2019): 48–76. http://dx.doi.org/10.4018/ijicst.2019010104.

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The distributed networking system is a dominant paradigm in the industry. In today's network industry, security and Quality of service (QoS) are two key services. The distributed network deals with an entire range of parameters coming from different applications. Therefore, it is of great significance to determine a set of key parameters and draw meaningful evaluation outcomes. On the other hand, security mechanisms provide user identification, authentication, consistency and information protection over the distributed environment. This research presents some analyses which draw connections between QoS and security of distributed networks. Then, a metric-based quantifying methodology is presented which quantifies network quality using QoS and security metrics. The QoS quantifying method is then further elaborated. The efficiency of this method is investigated using a range of simulation studies. The simulation analysis and results indicate that the proposed approach facilitates better QoS management and monitoring of the distributed networking systems.

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Hu, Hao, Yuling Liu, Hongqi Zhang, and Yuchen Zhang. "Security Metric Methods for Network Multistep Attacks Using AMC and Big Data Correlation Analysis." Security and Communication Networks 2018 (August 2, 2018): 1–14. http://dx.doi.org/10.1155/2018/5787102.

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Network security metrics allow quantitatively evaluating the overall resilience of networked systems against attacks. From this aim, security metrics are of great importance to the security-related decision-making process of enterprises. In this paper, we employ absorbing Markov chain (AMC) to estimate the network security combining with the technique of big data correlation analysis. Specifically, we construct the model of AMC using a large amount of alert data to describe the scenario of multistep attacks in the real world. In addition, we implement big data correlation analysis to generate the transition probability matrix from alert stream, which defines the probabilities of transferring from one attack action to another according to a given scenario before reaching one of some attack targets. Based on the probability reasoning, two metric algorithms are designed to estimate the attack scenario as well as the attackers, namely, the expected number of visits (ENV) and the expected success probability (ESP). The superiority is that the proposed model and algorithms assist the administrator in building new scenarios, prioritizing alerts, and ranking them.

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Novikova, Evgenia, Elena Doynikova, Diana Gaifulina, and Igor Kotenko. "Construction and Analysis of Integral User-Oriented Trustworthiness Metrics." Electronics 11, no. 2 (January 12, 2022): 234. http://dx.doi.org/10.3390/electronics11020234.

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Trustworthiness metrics help users to understand information system’s or a device’s security, safety, privacy, resilience, and reliability level. These metrics have different types and natures. The challenge consists of the integration of these metrics into one clear, scalable, sensitive, and reasonable metric representing overall trustworthiness level, useful for understanding if the users can trust the system or for the comparison of the devices and information systems. In this research, the authors propose a novel algorithm for calculation of an integral trustworthiness risk score that is scalable to any number of metrics, considers their criticality, and does not perform averaging in a case when all metrics are of equal importance. The obtained trustworthiness risk score could be further transformed to trustworthiness level. The authors analyze the resulting integral metric sensitivity and demonstrate its advantages on the series of experiments.

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Din, Roshidi, Rosmadi Bakar, Azizan Ismail, Aida Mustapha, and Sunariya Utama. "Evaluation review of effectiveness and security metrics performance on information technology domain." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 2 (November 1, 2019): 1059. http://dx.doi.org/10.11591/ijeecs.v16.i2.pp1059-1064.

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<p>Information Technology (IT) development is the vital required for human life activities in this global era. This implementation of IT system has becomes competitive among developers to increase the quality of system performance. In order to discover the IT performance of system, it neccesary to evaluate the IT implementation performance. It determines the anticipated system output to prepare to enhance the application performance. In this paper the evaluation performance that is reviewd are effectiveness and security metrics because both of evaluations able to improve the development and protection of system. Therefore, this paper classifies some IT domain development that used in term of effectiveness and security metric approach from previous researchers’ effort. It is categorized the domain based on both evaluation term of effectiveness and security metrics from specific parameter their used. The concern of this paper is to discover the important effectiveness and security metrics in IT domain performance that is anticipated to achieve expected performance.</p>

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Chubaievskyi, Vitaliy, Valery Lakhno, Olena Kryvoruchko, Dmytro Kasatkin, Alona Desiatko, Andrii Blozva, and Boris Gusev. "EFFICIENCY OF THE INDICATORS INVESTMENT CALCULATION METHOD IN THE INFORMATION SECURITY SYSTEM OF INFORMATION OBJECTS." Cybersecurity: Education, Science, Technique 1, no. 13 (2021): 16–28. http://dx.doi.org/10.28925/2663-4023.2021.13.1628.

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The article describes the methodology of multi-criteria optimization of costs for the information protection system of the object of informatization. The technique is based on the use of a modified VEGA genetic algorithm. A modified algorithm for solving the MCO problem of parameters of a multi-circuit information protection system of an informatization object is proposed, which makes it possible to substantiate the rational characteristics of the ISS components, taking into account the priority metrics of OBI cybersecurity selected by the expert. In contrast to the existing classical VEGA algorithm, the modified algorithm additionally applies the Pareto principle, as well as a new mechanism for the selection of population specimens. The Pareto principle applies to the best point. At this point, the solution, interpreted as the best, if there is an improvement in one of the cybersecurity metrics, and strictly no worse in another metric (or metrics). The new selection mechanism, in contrast to the traditional one, involves the creation of an intermediate population. The formation of an intermediate population occurs in several stages. At the first stage, the first half of the population is formed based on the metric - the proportion of vulnerabilities of the object of informatization that are eliminated in a timely manner. At the second stage, the second half of the intermediate population is formed based on the metric - the proportion of risks that are unacceptable for the information assets of the informatization object. Further, these parts of the intermediate population are mixed. After mixing, an array of numbers is formed and mixed. At the final stage of selection for crossing, specimens (individuals) will be taken by the number from this array. The numbers are chosen randomly. The effectiveness of this technique has been confirmed by practical results

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Zhang, Jing, Han-ying Hu, Min Tong, and Qing-rong Li. "A Security Metric and Related Security Routing Algorithm Design Based on Trust Model." Journal of Electronics & Information Technology 30, no. 1 (February 17, 2011): 10–15. http://dx.doi.org/10.3724/sp.j.1146.2007.00726.

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Jekl, Jan, and Jiří Jánský. "Security Challenges and Economic-Geographical Metrics for Analyzing Safety to Achieve Sustainable Protection." Sustainability 14, no. 22 (November 16, 2022): 15161. http://dx.doi.org/10.3390/su142215161.

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In this article, we aim to develop the theoretical background for the possible application of Economic-Geographical metrics in the field of population protection. We deal with various options for analyzing the availability of “safety” for citizens using studied metrics. Among others, we apply well-known metrics such as the Gini coefficient, Hoover index and even establish their generalizations. We develop a theoretical background and evaluate our findings on generated and actual data. We find that the metrics used can have an opposite interpretation depending on the scenario we are considering. We also discover that some scenarios demand a modification to the usual metric. We conclude that Economic-Geographical metrics give valuable tools to address specific security challenges. Metric’s generalizations could serve as a potent tool for other authors working in the field of population protection. Nevertheless, we must keep in mind that metrics also have drawbacks.

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Sharma Gaur, Madhu, and Bhaskar Pant. "Trust Metric based Soft Security in Mobile Pervasive Environment." International Journal of Computer Network and Information Security 6, no. 10 (September 8, 2014): 64–71. http://dx.doi.org/10.5815/ijcnis.2014.10.08.

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Agrawal, A. "Software Security Metric Development Framework (An Early Stage Approach)." American Journal of Software Engineering and Applications 2, no. 6 (2013): 150. http://dx.doi.org/10.11648/j.ajsea.20130206.14.

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Mukherjee, Preetam, and Chandan Mazumdar. "“Security Concern” as a Metric for Enterprise Business Processes." IEEE Systems Journal 13, no. 4 (December 2019): 4015–26. http://dx.doi.org/10.1109/jsyst.2019.2918116.

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Zonouz, Saman A., Robin Berthier, Himanshu Khurana, William H. Sanders, and Tim Yardley. "Seclius: An Information Flow-Based, Consequence-Centric Security Metric." IEEE Transactions on Parallel and Distributed Systems 26, no. 2 (February 2015): 562–73. http://dx.doi.org/10.1109/tpds.2013.162.

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Almasizadeh, Jaafar, and Mohammad Abdollahi Azgomi. "Mean privacy: A metric for security of computer systems." Computer Communications 52 (October 2014): 47–59. http://dx.doi.org/10.1016/j.comcom.2014.06.009.

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Purohit, Neha, Shubhalaxmi Joshi, Milind Pande, and Susan Lincke. "Pragmatic analysis of ECC based security models from an empirical perspective." Journal of Discrete Mathematical Sciences & Cryptography 26, no. 3 (2023): 739–58. http://dx.doi.org/10.47974/jdmsc-1749.

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This paper provides a detailed discussion about currently proposed Elliptic Curve Cryptography (ECC) models focusing on performance parameters such as Security, Complexity, Scalability, and cost of deployment. It was observed that Machine Learning optimizations including bio inspired computing, deep learning, and transformation models outperform other techniques. This discussion is extended via an empirical estimation of these models related to the performance metrics under different application scenarios. This paper also proposes the calculation of an ECC Performance Metric (EPM), which combines the evaluated parameter sets to identify ECC Models that can perform better under multiple operating scenarios.

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Rakovskiy, Dmitriy I. "Influence of multi&label class problem of system logs on the security of computer networks." H&ES Research 15, no. 1 (2023): 48–56. http://dx.doi.org/10.36724/2409-5419-2023-15-1-48-56.

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The security of information circulating in a computer network is related to the security of the supporting infrastructure. An important problem in the intelligent processing of syslog data is the existence of multi-label datasets. Among the Russian-language scientific publications, the problem under consideration in the context of information security of computer networks is not presented. Purpose: increase the security of computer networks by using multi-label learning methods when solving the problem of classifying system logs class labels. Results: A comparative analysis of single-valued and multi-label classifiers was carried out in a computational experiment on the Mean accuracy metric. A non-linear relationship was found between the proportion of experimental data sections containing multi-label class labels and the overall accuracy of data classification. Despite the fact that multilabel plots in the studied experimental data are only 3%, the gain in accuracy reaches 23% according to the specified metric. According to the results of the analysis, 80% of unambiguous classifiers were inferior in classification accuracy according to the Mean accuracy multi-label metric to their analogues, which may signal a strong influence of multi-label class labels on the models under consideration. It is shown that the considered structure of experimental data in a tabular form is affected by the multi-label problem much more strongly than it can be estimated by a standard frequency check, which actualizes further research in this direction. Practical relevance: The practical significance of the results obtained lies in increasing the security of computer networks through the use of a multi-label approach in the classification problem. The tasks of information security solved by multi-label classification may include: the area of monitoring, detection or prevention of violations and computer attacks in computer networks. Discussion: Since the predictive power of frequency testing of the influence of multi-label class label results on the classification results of unambiguous classifiers is low, further research on this topic is planned. It is planned to expand the list of classification quality assessment metrics in future experiments.

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Casola, Valentina, Antonino Mazzeo, Nicola Mazzocca, and Valeria Vittorini. "A policy-based methodology for security evaluation: A Security Metric for Public Key Infrastructures." Journal of Computer Security 15, no. 2 (February 5, 2007): 197–229. http://dx.doi.org/10.3233/jcs-2007-15201.

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Dobrowolski, Zbysław, and Grzegorz Drozdowski. "Does the Net Present Value as a Financial Metric Fit Investment in Green Energy Security?" Energies 15, no. 1 (January 4, 2022): 353. http://dx.doi.org/10.3390/en15010353.

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Surprisingly, little is known whether the net present value (NPV) used as a financial metric in budgeting and investment planning to analyse a projects’ profitability is universal. Meanwhile, the epochal green energy revolution ensuring carbon neutrality through green innovations requires enormous investments, and projects realised must ensure energy security. Therefore, there is a need to reanalyse financial metrics used in financial planning, including NPV. We eliminate this research gap and, based on data from Poland, Romania, Hungary, Croatia, the USA, the United Kingdom, Japan, Israel, and Euro Zone, explain why one may not perceive the currently used NPV formula as a universal financial metric. We show that the variable discount rate influences the time value of money. Therefore, there is a need to redefine the NPV formula. This study makes two main contributions. First, it creates new ground by revisiting the NPV formula in the emerging market context compared to stable economies and contributes to developing business and management theory. Second, we propose and empirically verify the modified NPV formula as a financial metric that considers the situation of energy firms in emerging markets. Thus, this research helps the capital budgeting process, and the modified NPV formula can help provide optimal outcomes in firms, helping to reduce financial risks. Our study contributes to a further contextual diagnosis of business projects and can, in turn, be relevant for other energy sector analyses.

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Chen, Hongsong, Haiyan Zhuang, Zhiguang Shan, Chao-Hsien Lee, and Zhongchuan Fu. "A novel SMP-based survivability evaluation metric and approach in wireless sensor network." Computer Science and Information Systems 16, no. 3 (2019): 733–51. http://dx.doi.org/10.2298/csis180918024c.

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In Industrial Internet of Things (IIoT) device and network, wireless sensor network (WSN) is an important component. Routing protocol is the critical component of WSN. As the WSN may be attacked by all kinds of intruders, the survivability of WSN is important to IIoT security. To precisely evaluate the systematic survivability ability under external attack and internal security mechanism, a novel survivability entropy-based quantitative evaluation metric is proposed to calculate the systematic survivability ability of WSN routing protocol. Numerical analysis and simulation experiments are combined to precisely calculate the survivability entropy metric. To validate the evaluation approach, NS2 (Network simulator) is used to simulate the DoS attack and security mechanism in WSN. Experimental results show that the novel survivability evaluation metric and method can precisely evaluate the systematic survivability ability of WSN.

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Yevseiev, Serhii, Oleksandr Milov, Ivan Opirskyy, Olha Dunaievska, Oleksandr Huk, Volodymyr Pogorelov, Kyrylo Bondarenko, Nataliia Zviertseva, Yevgen Melenti, and Bogdan Tomashevsky. "Development of a concept for cybersecurity metrics classification." Eastern-European Journal of Enterprise Technologies 4, no. 4 (118) (August 31, 2022): 6–18. http://dx.doi.org/10.15587/1729-4061.2022.263416.

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The development of the IT industry and computing resources allows the formation of cyberphysical social systems (CPSS), which are the integration of wireless mobile and Internet technologies and the combination of the Internet of things with the technologies of cyberphysical systems. To build protection systems, while minimizing both computing and economic costs, various sets of security profiles are used, ensuring the continuity of critical business processes. To assess/compare the level of CPSS security, various assessment methods based on a set of metrics are generally used. Security metrics are tools for providing up-to-date information about the state of the security level, cost characteristics/parameters from both the defense and attack sides. However, the choice of such sets is not always the same/understandable to the average person. This, firstly, leads to the absence of a generally accepted and unambiguous definition, which means that one system is more secure than another. Secondly, it does not take into account the signs of synergy and hybridity of modern targeted attacks. Without this knowledge, it is impossible to show that the metric measures the security level objectively. Thirdly, there is no universal formal model for all metrics that could be used for rigorous analysis. The paper explores the possibility of defining a basic formal model (classifier) for analyzing security metrics. The proposed security assessment model takes into account not only the level of secrecy of information resources, the level of provision of security services, but also allows, based on the requirements put forward, forming the necessary set of security assessment metrics, taking into account the requirements for the continuity of business processes. The average value of the provision of security services to CPSS information resources is 0.99, with an average value of the security level of information resources of 0.8

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Shen, Danyao, Fengchao Zhu, Zhanpeng Zhang, and Xiaodong Mu. "Radio Frequency Fingerprint Identification Based on Metric Learning." International Journal of Information Technologies and Systems Approach 16, no. 3 (April 13, 2023): 1–13. http://dx.doi.org/10.4018/ijitsa.321194.

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With the popularization of the internet of things (IoT), its security has become increasingly prominent. Radio-frequency fingerprinting (RFF) is used as a physical-layer security method to provide security in wireless networks. However, the problems of poor performance in a highly noisy environment and less consideration of calculation resources are urgent to be resolved in a practical RFF application domain. The authors propose a new RFF identification method based on metric learning. They used power spectrum density (PSD) to extract the RFF from the nonlinearity of the RF front end. Then they adopted the large margin nearest neighbor (LMNN) classification algorithm to identify eight software-defined radio (SDR) devices. Different from existing RFF identification algorithms, the proposed LMNN method is more general and can learn the optimal metric from the wireless communication environment. Furthermore, they propose a new training and test strategy based on mixed SNR, which significantly improves the performance of conventional low-complexity RFF identification methods. Experimental results show that the proposed method can achieve 99.8% identification accuracy with 30dB SNR and 96.83% with 10dB SNR. In conclusion, the study demonstrates the effectiveness of the proposed method in recognition efficiency and computational complexity.

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Park, Ui Hyun, Jeong-hyeop Hong, Auk Kim, and Kyung Ho Son. "Endpoint Device Risk-Scoring Algorithm Proposal for Zero Trust." Electronics 12, no. 8 (April 18, 2023): 1906. http://dx.doi.org/10.3390/electronics12081906.

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The rapid expansion of remote work following the COVID-19 pandemic has necessitated the development of more robust and secure endpoint device security solutions. Companies have begun to adopt the zero trust security concept as an alternative to traditional network boundary security measures, which requires that every device and user be considered untrustworthy until proven otherwise. Despite the potential benefits of implementing zero trust, the stringent security measures can inadvertently lead to low availability by denying access to legitimate users or limiting their ability to access necessary resources. To address this challenge, we propose a risk-scoring algorithm that balances confidentiality and availability by evaluating the user’s impact on resources. Our contributions include (1) summarizing the limitations of existing risk scoring systems in companies that implement zero trust, (2) proposing a dynamic importance metric that measures the importance of resources accessible to users within zero trust systems, and (3) introducing a risk-scoring algorithm that employs the dynamic importance metric to enhance both security and availability in zero trust environments. By incorporating the dynamic importance metric, our proposed algorithm provides a more accurate representation of risk, leading to better security decisions and improved resource availability for legitimate users. This proposal aims to help organizations achieve a more balanced approach to endpoint device security, addressing the unique challenges posed by the increasing prevalence of remote work.

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Rehman, Eid, Muhammad Sher, Syed Hussnain Abbas Naqvi, Khan Badar Khan, and Kamran Ullah. "Energy Efficient Secure Trust Based Clustering Algorithm for Mobile Wireless Sensor Network." Journal of Computer Networks and Communications 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/1630673.

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The main benefit of selecting a suitable node as cluster head (CH) in clustering for wireless mobile sensor networks (MWSNs) is to prolong the network lifetime. But the safe selection of CH is a challenging task by taking security into account. Mostly CH selection algorithms in MWSN do not consider security when selecting CH. We have proposed secure CH selection algorithm by calculating weight of each node to deal with secure selection using minimum energy consumption. The weight of node is a combination of different metrics including trust metric (behaviors of sensor node) which promotes a secure decision of a CH selection; in terms of this, the node will never be a malicious one. The trust metric is definitive and permits the proposed clustering algorithm to keep away from any malignant node in the area to select a CH, even if the rest of the parameters are in its favor. Other metrics of node include waiting time, connectivity degree, and distance among nodes. The selection of CHs is completed utilizing weights of member nodes. The preparatory outcomes acquired through simulation exhibit the adequacy of our proposed scheme as far as average rate of avoiding malicious node as a CH, energy efficiency, and some other performance parameters are concerned.

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Lau, Terry Shue Chien, and Chik How Tan. "On the design and security of Lee metric McEliece cryptosystems." Designs, Codes and Cryptography 90, no. 3 (January 18, 2022): 695–717. http://dx.doi.org/10.1007/s10623-021-01002-2.

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RajaSekhar, K., L. S. S. Reddy, and U. J. Kameswari. "Secure System of Attack Patterns towards Application Security Metric Derivation." International Journal of Computer Applications 53, no. 1 (September 25, 2012): 11–18. http://dx.doi.org/10.5120/8384-1987.

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Schwartau, Winn. "Network Security It’s About Time: An Offer for a Metric." Network Security 2001, no. 8 (August 2001): 11–13. http://dx.doi.org/10.1016/s1353-4858(01)00815-7.

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Simpson, Joseph J., Ann Miller, and Cihan H. Dagli. "6.3.1 Secure Adaptive Response Potential (SARP): A System Security Metric." INCOSE International Symposium 18, no. 1 (June 2008): 706–19. http://dx.doi.org/10.1002/j.2334-5837.2008.tb00838.x.

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Ghobrial, Atef, and Theodore H. Poister. "Evaluating security of rail transit systems: A metric system approach." Journal of Advanced Transportation 29, no. 2 (March 1995): 251–62. http://dx.doi.org/10.1002/atr.5670290208.

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Khan, Salman A., Kashif Iqbal, Nazeeruddin Mohammad, Rehan Akbar, Syed Saad Azhar Ali, and Ammar Ahmed Siddiqui. "A Novel Fuzzy-Logic-Based Multi-Criteria Metric for Performance Evaluation of Spam Email Detection Algorithms." Applied Sciences 12, no. 14 (July 12, 2022): 7043. http://dx.doi.org/10.3390/app12147043.

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The increasing volume of unsolicited bulk emails has become a major threat to global security. While a significant amount of research has been carried out in terms of proposing new and better algorithms for email spam detection, relatively less attention has been given to evaluation metrics. Some widely used metrics include accuracy, recall, precision, and F-score. This paper proposes a new evaluation metric based on the concepts of fuzzy logic. The proposed metric, termed μO, combines accuracy, recall, and precision into a multi-criteria fuzzy function. Several possible evaluation rules are proposed. As proof of concept, a preliminary empirical analysis of the proposed scheme is carried out using two models, namely BERT (Bidirectional Encoder Representations from Transformers) and LSTM (Long short-term memory) from the domain of deep learning, while utilizing three benchmark datasets. Results indicate that for the Enron and PU datasets, LSTM produces better results of μO, with the values in the range of 0.88 to 0.96, whereas BERT generates better values of μO in the range of 0.94 to 0.96 for Lingspam dataset. Furthermore, extrinsic evaluation confirms the effectiveness of the proposed fuzzy logic metric.

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Yeremenko, Oleksandra, Mykhailo Persikov, Valentyn Lemeshko, and Bassam Altaki. "Research and Development of the Secure Routing Flow-Based Model with Load Balancing." Problemi telekomunìkacìj, no. 2(29) (December 22, 2021): 3–14. http://dx.doi.org/10.30837/pt.2021.2.01.

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The article is devoted to developing and researching the model of secure routing with load balancing in SD-WAN-based networks. In addition, an analysis of numerical research results using Python, GEKKO Optimization Suite, and NumPy has been carried out. The technical task of secure routing with load balancing was formulated as an optimization problem with quadratic optimality criterion. Such a criterion form allows for balancing the flow shares transmitting in the network. The simulation results showed that the link load (namely, the transmitted part of the flow) under study decreases with an increased probability of the link compromise. The analysis of the calculated results revealed the value of the security and performance ratio metric when the model is most sensitive to the network link compromise probability deterioration. That is, the best sensitivity of the model to the network security indicator (compromise probability) appears when the ratio between performance and security metric takes values of 100 to 300. Therefore, the presented model of secure routing with load balancing with an additive metric that accounts for network performance and security allows using network resources more efficiently but also considers the link compromise probability in making routing decisions.

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Tkaczyk, Zoé, and William G. Moseley. "Dietary Power and Self-Determination among Female Farmers in Burkina Faso: A Proposal for a Food Consumption Agency Metric." Land 12, no. 5 (April 28, 2023): 978. http://dx.doi.org/10.3390/land12050978.

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Although food security is traditionally defined with four dimensions, there are increasing calls for an additional two: agency and sustainability. However, it is especially challenging to measure agency, a person’s control over their food production and consumption. Measuring women’s agency is especially critical in African regions south of the Sahara, where women play prominent roles in farming and food preparation. This paper explores the feasibility of creating a metric to measure agency within food systems using data related to food security and dietary diversity among female rice farmers in southwestern Burkina Faso. Informed by the literature on agency, autonomy, and food sovereignty, we developed an agency index based upon a subset of questions in the Household Food Insecurity Access Scale (HFIAS). We call this metric the Food Consumption Agency Metric (FCAM). By applying the FCAM, we then sought to understand how agency complements our understanding and measurement of food security. In exploring the relationship between agency and food security more broadly, we found that agency can be quantified in a way that increases its accessibility to policymakers to create more just food systems and expand how we approach food justice.

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Yin, Lihua, Yanwei Sun, Zhen Wang, Yunchuan Guo, Fenghua Li, and Binxing Fang. "Security Measurement for Unknown Threats Based on Attack Preferences." Security and Communication Networks 2018 (2018): 1–13. http://dx.doi.org/10.1155/2018/7412627.

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Security measurement matters to every stakeholder in network security. It provides security practitioners the exact security awareness. However, most of the works are not applicable to the unknown threat. What is more, existing efforts on security metric mainly focus on the ease of certain attack from a theoretical point of view, ignoring the “likelihood of exploitation.” To help administrator have a better understanding, we analyze the behavior of attackers who exploit the zero-day vulnerabilities and predict their attack timing. Based on the prediction, we propose a method of security measurement. In detail, we compute the optimal attack timing from the perspective of attacker, using a long-term game to estimate the risk of being found and then choose the optimal timing based on the risk and profit. We design a learning strategy to model the information sharing mechanism among multiattackers and use spatial structure to model the long-term process. After calculating the Nash equilibrium for each subgame, we consider the likelihood of being attacked for each node as the security metric result. The experiment results show the efficiency of our approach.

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Segura Smith, Andrea, Julie Porter, Amogh Badwe, Eileen F. Kiamanesh, and Douglas W. Blayney. "Quality, clinician and information technology (IT) partnership for metric reporting." Journal of Clinical Oncology 35, no. 8_suppl (March 10, 2017): 128. http://dx.doi.org/10.1200/jco.2017.35.8_suppl.128.

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128 Background: Reporting of physician defined quality metrics, using manual data abstraction, is labor intensive and not always timely. We developed a multidisciplinary team to develop a metric reporting system. Methods: The Senior Quality Consultant (SQC) partnered with the Research Data Analyst using data extracted from the electronic data warehouse, Bone Marrow Transplant Registry, Cancer Registry, Aria (Varian, Palo Alto) and Epic (Verona, WI) and the Social Security Death index. The Plan, Do, Check Act model was used to guide the team. Results: Fourteen metrics were developed in a seven-month period. Sample of metrics: Blood Marrow Transplant patient referral to Survivorship by Day 100; Genetic counseling referral for ovarian cancer; Cytogenetic testing of acute leukemia, myeloma; Chemotherapy in the last two weeks of life; Hospice enrollment at death; > 10 radiation fractions for bone metastases palliation. Conclusions: The PDCA model created a shared framework for metric development. Standard definitions were developed and applied to promote consistent design. 72% (10/14) of the metrics are on a reporting system for automated data extraction and reporting. The limitation of the project is negative results are reviewed manually by the SQC because not all data elements are discrete and may require review of items (ex. progress notes or media). [Table: see text]

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Tashtoush, Yahya M., Aisha Zaidan, and Izzat M. Alsmadi. "Implications for Website Trust and Credibility Assessment." International Journal of E-Entrepreneurship and Innovation 3, no. 4 (October 2012): 17–33. http://dx.doi.org/10.4018/jeei.2012100102.

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With the expansion of the Internet services provided to users to cover almost all areas that were dominated by traditional face-to-face and location based businesses, one of the major challenges for such expansion is security and its related concerns. Customers or users need to trust the websites they visit in terms of the information or content. This research proposes a new formula for evaluating the credibility (called XD TRank) metric of websites. A case study of 40 selected websites in Jordan is used to assess the proposed credibibility metric. The metrics required to assess Websites and pages credibility are collected and evaluated based on 25 existing metrics and built a model using SPSS by applying stepwise linear regression analysis to predict the XD TRank. Results showed that there is a broad range of metrics that affect the credibility of a website or a webpage and their impact on credibility may vary on their significancy or impact on the trust rank metric. For e-business in particular, trust rank metrics can be used part of quality assurance and auditing processes. Those can be important assets for users to be able to distinguish known, popular and reliable e-commerce websites from spammers or websites which try to trick novice users. Trust rank can be also used like a logo in all Website pages to alert users if they were redirected to phishing pages.

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Ramanauskaitė, Simona, Neringa Urbonaitė, Šarūnas Grigaliūnas, Saulius Preidys, Vaidotas Trinkūnas, and Algimantas Venčkauskas. "Educational Organization’s Security Level Estimation Model." Applied Sciences 11, no. 17 (August 31, 2021): 8061. http://dx.doi.org/10.3390/app11178061.

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During the pandemic, distance learning gained its necessity. Most schools and universities were forced to use e-learning tools. The fast transition to distance learning increased the digitalization of the educational system and influenced the increase of security incident numbers as there was no time to estimate the security level change by incorporating new e-learning systems. Notably, preparation for distance learning was accompanied by several limitations: lack of time, lack of resources to manage the information technologies and systems, lack of knowledge on information security management, and security level modeling. In this paper, we propose a security level estimation model for educational organizations. This model takes into account distance learning specifics and allows quantitative estimation of an organization’s security level. It is based on 49 criteria values, structured into an AHP (Analytic Hierarchy Process) tree, and arranged to final security level metric by incorporating experts’ opinion-based criteria importance coefficients. The research proposed a criteria tree and obtained experts’ opinions lead to educational organization security level evaluation model, resulting in one quantitative metric. It can be used to model different situations and find the better alternative in case of security level, without external security experts usage. Use case analysis results and their similarity to security experts’ evaluation are presented in this paper as validation of the proposed model. It confirms the model meets experts-based information security level ranking, therefore, can be used for simpler security modeling in educational organizations.

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Journal articles on the topic 'Metric Security'

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