Relevant bibliographies by topics / Automatic countermeasures

Academic literature on the topic 'Automatic countermeasures'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Automatic countermeasures"

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Bayrak, Ali Galip, Francesco Regazzoni, David Novo, Philip Brisk, Francois-Xavier Standaert, and Paolo Ienne. "Automatic Application of Power Analysis Countermeasures." IEEE Transactions on Computers 64, no. 2 (February 2015): 329–41. http://dx.doi.org/10.1109/tc.2013.219.

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Wojtal, Remigiusz M., and Laurence R. Rilett. "Development of a statistically-based methodology for analyzing automatic safety treatments at isolated high-speed signalized intersections." Archives of Transport 44, no. 4 (November 30, 2017): 75–88. http://dx.doi.org/10.5604/01.3001.0010.6163.

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Crashes at isolated rural intersections, particularly those involving vehicles traveling perpendicularly to each other, are especially dangerous due to the high speeds involved. Consequently, transportation agencies are interested in reducing the occurrence of this crash type. Many engineering treatments exist to improve safety at isolated, high-speed, signalized intersections. Intuitively, it is critical to know which safety treatments are the most effective for a given set of selection criteria at a particular intersection. Without a well-defined decision making methodology, it is difficult to decide which safety countermeasure, or set of countermeasures, is the best option. Additionally, because of the large number of possible intersection configurations, traffic volumes, and vehicle types, it would be impossible to develop a set of guidelines that could be applied to all signalized intersections. Therefore, a methodology was developed in in this paper whereby common countermeasures could be modeled and analyzed prior to being implemented in the field. Due to the dynamic and stochastic nature of the problem, the choice was made to employ microsimulation tools, such as VISSIM, to analyze the studied countermeasures. A calibrated and validated microsimulation model of a signalized intersection was used to model two common safety countermeasures. The methodology was demonstrated on a test site located just outside of Lincoln, Nebraska. The model was calibrated to the distribution of observed speeds collected at the test site. It was concluded that the methodology could be used for the preliminary analysis of safety treatments based on select safety and operational measures of effectiveness.
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Wang, Fang, and Wei Zhang. "OTU Plate Heat Countermeasures of Automatic Test Platform Design." Advanced Materials Research 740 (August 2013): 676–79. http://dx.doi.org/10.4028/www.scientific.net/amr.740.676.

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By improving the optical module internal thermal test platform for media and increase cooling efficiency, solve LASER_TCT/CCT OTU class plate temperature warning faults such as, and has been tested. Test results showed that the improvement to meet design requirements.
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Hu, Shengshan, Xingcan Shang, Zhan Qin, Minghui Li, Qian Wang, and Cong Wang. "Adversarial Examples for Automatic Speech Recognition: Attacks and Countermeasures." IEEE Communications Magazine 57, no. 10 (October 2019): 120–26. http://dx.doi.org/10.1109/mcom.2019.1900006.

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Wu, Zhizheng, Junichi Yamagishi, Tomi Kinnunen, Cemal Hanilci, Mohammed Sahidullah, Aleksandr Sizov, Nicholas Evans, Massimiliano Todisco, and Hector Delgado. "ASVspoof: The Automatic Speaker Verification Spoofing and Countermeasures Challenge." IEEE Journal of Selected Topics in Signal Processing 11, no. 4 (June 2017): 588–604. http://dx.doi.org/10.1109/jstsp.2017.2671435.

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Kinnunen, Tomi, Hector Delgado, Nicholas Evans, Kong Aik Lee, Ville Vestman, Andreas Nautsch, Massimiliano Todisco, et al. "Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verification: Fundamentals." IEEE/ACM Transactions on Audio, Speech, and Language Processing 28 (2020): 2195–210. http://dx.doi.org/10.1109/taslp.2020.3009494.

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Yamagishi, Junichi, Tomi H. Kinnunen, Nicholas Evans, Phillip De Leon, and Isabel Trancoso. "Introduction to the Issue on Spoofing and Countermeasures for Automatic Speaker Verification." IEEE Journal of Selected Topics in Signal Processing 11, no. 4 (June 2017): 585–87. http://dx.doi.org/10.1109/jstsp.2017.2698143.

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Altuwayjiri, Sarah Mohammed, Ouiem Bchir, and Mohamed Maher Ben Ismail. "Generalized Replay Spoofing Countermeasure Based on Combining Local Subclassification Models." Applied Sciences 12, no. 22 (November 18, 2022): 11742. http://dx.doi.org/10.3390/app122211742.

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Automatic speaker verification (ASV) systems play a prominent role in the security field due to the usability of voice biometrics compared to alternative biometric authentication modalities. Nevertheless, ASV systems are susceptible to malicious voice spoofing attacks. In response to such threats, countermeasures have been devised to prevent breaches and ensure the safety of user data by categorizing utterances as either genuine or spoofed. In this paper, we propose a new voice spoofing countermeasure that seeks to improve the generalization of supervised learning models. This is accomplished by alleviating the problem of intraclass variance. Specifically, the proposed approach addresses the generalization challenge by splitting the classification problem into a set of local subproblems in order to lessen the supervised learning task. The system outperformed existing state-of-the-art approaches with an EER of 0.097% on the ASVspoof challenge corpora related to replaying spoofing attacks.
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You Yu, Huang. "Research on Psychological Problems and Countermeasures of Contemporary College Students Based on Data Analysis." Mobile Information Systems 2022 (February 23, 2022): 1–7. http://dx.doi.org/10.1155/2022/3366837.

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Due to absence of good and high prevalence rate of the comprehensive method of automatic assessment, the current mental health assessment is still subject to manual answer questionnaires. The main drawback of this is that the detection of mental health issues of contemporary college students through the manual answer questionnaire is not satisfactory. Mental health problems of the students cannot be properly detected, and as a result, they remain deprived of timely psychological counseling and treatment. At the same time, in order to improve the accuracy of automatic selection of mental health and the popularity of this solution, this study first presents a detailed analysis of the possible mental health problems encountered by contemporary college students. A radial basis function (radial basis function, RBF) neural network application in the automatic selection of mental health status and comparative verification. The results proved the higher accuracy and warning of the RBF nervous system in comparison to the mental health of contemporary college students. The research further investigates the dependence of the psychological problems and solutions of contemporary college students on data analysis. It can be rightly said that the study is of great importance due to its provision of new research direction and relevant countermeasures for the psychological problems of college students.
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Alam. "On the Use of Fisher Vector Encoding for Voice Spoofing Detection." Proceedings 31, no. 1 (November 20, 2019): 37. http://dx.doi.org/10.3390/proceedings2019031037.

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Recently, the vulnerability of automatic speaker recognition systems to spoofing attacks has received significant interest among researchers. A robust speaker recognition system demands not only high recognition accuracy but also robustness to spoofing attacks. Several spoofing and countermeasure challenges have been organized to draw attention to this problem among the speaker recognition communities. Low-level descriptors designed to detect artifacts in spoofed speech are found to be the most effective countermeasures against spoofing attacks. In this work, we used Fisher vector encoding of low-level descriptors extracted from speech signals. The idea behind Fisher vector encoding is to determine the amount of change induced by the descriptors of the signal on a background probability model which is typically a Gaussian mixture model. The Fisher vector encodes the amount of change of the model parameters to optimally fit the new- coming data. For performance evaluation of the proposed approach we carried out spoofing detection experiments on the 2015 edition of automatic speaker verification spoofing and countermeasure challenge (ASVspoof2015) and report results on the evaluation set. As baseline systems, we used the standard Gaussian mixture model and i-vector/PLDA paradigms. For a fair comparison, in all systems, Constant Q cepstral coefficient (CQCC) features were used as low-level descriptors. With the Fisher vector-based approach, we achieved an equal error rate (EER) of 0.1145% on the known attacks, 1.223% on the unknown attacks, and 0.668% on the average. Moreover, with a single decision threshold this approach yielded an EER of 1.05% on the evaluation set.
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Dissertations / Theses on the topic "Automatic countermeasures"

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Neubauer, Catherine. "Alertness Maintaining Tasks: A Fatigue Countermeasure During Vehicle Automation?" University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1396522991.

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Fältros, Jesper, Isak Alinger, and Bergen Axel von. "Safety risks with ZigBee smart devices : Identifying risks and countermeasures in ZigBee devices with an eavesdropping experiment." Thesis, Tekniska Högskolan, Jönköping University, JTH, Datateknik och informatik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-49630.

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With ZigBee being the world’s leading IoT protocol, users are vulnerable to attacks on the wireless communication between ZigBee devices and the information that can be gained from them. For users to protect themselves from potential attacks they need to be aware of what information can be extracted and how it can be countered. Through an eavesdropping experiment, done using three individual sensors from different vendors, various packets with potential for misuse have been identified within the area of building security. With the potential areas of misuse identified, there is also a need for countermeasures against these threats. Countermeasures were identified through a collection of literature that was summarized in order to provide a wide range of alternatives, suitable to different scenarios. The experiment was limited to the functions of the sensors used, as well as traffic using the ZigBee protocol. This study pinpoints a potential for misuse of the ZigBee traffic sent between devices and shows that the ZigBee protocol is fundamentally flawed from a security aspect. Whilst countermeasures exist, they are not applicable to every situation which is why the ZigBee protocol itself needs further development to be considered secure.
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Veshchikov, Nikita. "Use of simulators for side-channel analysis: Leakage detection and analysis of cryptographic systems in early stages of development." Doctoral thesis, Universite Libre de Bruxelles, 2008. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/256648.

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Cryptography is the foundation of modern IT security,it provides algorithms and protocols that can be usedfor secure communications. Cryptographic algorithmsensure properties such as confidentiality and data integrity.Confidentiality can be ensured using encryption algorithms.Encryption algorithms require a secret information called a key.These algorithms are implemented in cryptographic devices.There exist many types of attacks against such cryptosystems,the main goal of these attacks is the extraction of the secret key.Side-channel attacks are among the strongest types of attacksagainst cryptosystems. Side-channel attacks focus on the attacked device, they measure its physicalproperties in order to extract the secret key. Thus, these attacks targetweaknesses in an implementation of an algorithm rather than the abstract algorithm itself.Power analysis is a type of side-channel attacks that can be used to extract a secretkey from a cryptosystem through the analysis of its power consumption whilethe target device executes an encryption algorithm. We can say that the secret information is leaking from the device through itspower consumption. One of the biggest challenges in the domain of side-channel analysisis the evaluation of a device from the perspective of side-channel attacksor in other words the detection of information leakage.A device can be subject to several sources of information leakageand it is actually relatively easy to find just one side-channel attack that works(by exploiting just one source of leakage),however it is very difficult to find all sources of information leakage or to show that there is no information leakage in the givenimplementation of an encryption algorithm. Evaluators use various statistical tests during the analysis of a cryptographic device to checkthat it does not leak the secret key. However, in order to performsuch tests the evaluation lab needs the device to acquire the measurementsand analyse them. Unfortunately, the development process of cryptographicsystems is rather long and has to go through several stages. Thus, an information leakagethat can lead to a side-channel attackcan be discovered by an evaluation lab at the very last stage using the finalproduct. In such case, the whole process has to be restarted in order to fix the issue,this can lead to significant time and budget overheads. The rationale is that developers of cryptographic systems would like to be able to detect issues related to side-channel analysis during the development of the system,preferably on the early stages of its development. However, it is far from beinga trivial task because the end product is not yet available andthe nature of side-channel attacks is such that it exploits the properties ofthe final version of the cryptographic device that is actually available to the end user. The goal of this work is to show how simulators can be used for the detection of issues related to side-channel analysis during the development of cryptosystems.This work lists the advantages of simulators compared to physical experimentsand suggests a classification of simulators for side-channel analysis.This work presents existing simulators that were created for side-channel analysis,more specifically we show that there is a lack of available simulation toolsand that therefore simulators are rarely used in the domain. We present threenew open-source simulators called Silk, Ascold and Savrasca.These simulators are working at different levels of abstraction,they can be used by developers to perform side-channel analysisof the device during different stages of development of a cryptosystem.We show how Silk can be used during the preliminary analysisand development of cryptographic algorithms using simulations based on high level of abstraction source code. We used it to compare S-boxesas well as to compare shuffling countermeasures against side-channel analysis.Then, we present the tool called Ascold that can be used to find side-channel leakagein implementations with masking countermeasure using the analysis of assembly code of the encryption.Finally, we demonstrate how our simulator called Savrasca can be used to find side-channelleakage using simulations based on compiled executable binaries. We use Savrascato analyse masked implementation of a well-known contest on side-channel analysis (the 4th edition of DPA Contest),as a result we demonstrate that the analysed implementation contains a previouslyundiscovered information leakage. Through this work we alsocompared results of our simulated experiments with real experiments comingfrom implementations on microcontrollers and showed that issues found using our simulatorsare also present in the final product. Overall, this work emphasises that simulatorsare very useful for the detection of side-channel leakages in early stages of developmentof cryptographic systems.
Option Informatique du Doctorat en Sciences
info:eu-repo/semantics/nonPublished
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Veshchikov, Nikita. "Use of simulators for side-channel analysis: Leakage detection and analysis of cryptographic systems in early stages of development." Doctoral thesis, Universite Libre de Bruxelles, 2017. https://dipot.ulb.ac.be/dspace/bitstream/2013/256648/3/final.pdf.

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Cryptography is the foundation of modern IT security,it provides algorithms and protocols that can be usedfor secure communications. Cryptographic algorithmsensure properties such as confidentiality and data integrity.Confidentiality can be ensured using encryption algorithms.Encryption algorithms require a secret information called a key.These algorithms are implemented in cryptographic devices.There exist many types of attacks against such cryptosystems,the main goal of these attacks is the extraction of the secret key.Side-channel attacks are among the strongest types of attacksagainst cryptosystems. Side-channel attacks focus on the attacked device, they measure its physicalproperties in order to extract the secret key. Thus, these attacks targetweaknesses in an implementation of an algorithm rather than the abstract algorithm itself.Power analysis is a type of side-channel attacks that can be used to extract a secretkey from a cryptosystem through the analysis of its power consumption whilethe target device executes an encryption algorithm. We can say that the secret information is leaking from the device through itspower consumption. One of the biggest challenges in the domain of side-channel analysisis the evaluation of a device from the perspective of side-channel attacksor in other words the detection of information leakage.A device can be subject to several sources of information leakageand it is actually relatively easy to find just one side-channel attack that works(by exploiting just one source of leakage),however it is very difficult to find all sources of information leakage or to show that there is no information leakage in the givenimplementation of an encryption algorithm. Evaluators use various statistical tests during the analysis of a cryptographic device to checkthat it does not leak the secret key. However, in order to performsuch tests the evaluation lab needs the device to acquire the measurementsand analyse them. Unfortunately, the development process of cryptographicsystems is rather long and has to go through several stages. Thus, an information leakagethat can lead to a side-channel attackcan be discovered by an evaluation lab at the very last stage using the finalproduct. In such case, the whole process has to be restarted in order to fix the issue,this can lead to significant time and budget overheads. The rationale is that developers of cryptographic systems would like to be able to detect issues related to side-channel analysis during the development of the system,preferably on the early stages of its development. However, it is far from beinga trivial task because the end product is not yet available andthe nature of side-channel attacks is such that it exploits the properties ofthe final version of the cryptographic device that is actually available to the end user. The goal of this work is to show how simulators can be used for the detection of issues related to side-channel analysis during the development of cryptosystems.This work lists the advantages of simulators compared to physical experimentsand suggests a classification of simulators for side-channel analysis.This work presents existing simulators that were created for side-channel analysis,more specifically we show that there is a lack of available simulation toolsand that therefore simulators are rarely used in the domain. We present threenew open-source simulators called Silk, Ascold and Savrasca.These simulators are working at different levels of abstraction,they can be used by developers to perform side-channel analysisof the device during different stages of development of a cryptosystem.We show how Silk can be used during the preliminary analysisand development of cryptographic algorithms using simulations based on high level of abstraction source code. We used it to compare S-boxesas well as to compare shuffling countermeasures against side-channel analysis.Then, we present the tool called Ascold that can be used to find side-channel leakagein implementations with masking countermeasure using the analysis of assembly code of the encryption.Finally, we demonstrate how our simulator called Savrasca can be used to find side-channelleakage using simulations based on compiled executable binaries. We use Savrascato analyse masked implementation of a well-known contest on side-channel analysis (the 4th edition of DPA Contest),as a result we demonstrate that the analysed implementation contains a previouslyundiscovered information leakage. Through this work we alsocompared results of our simulated experiments with real experiments comingfrom implementations on microcontrollers and showed that issues found using our simulatorsare also present in the final product. Overall, this work emphasises that simulatorsare very useful for the detection of side-channel leakages in early stages of developmentof cryptographic systems.
Option Informatique du Doctorat en Sciences
info:eu-repo/semantics/nonPublished
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Valičková, Monika. "Řízení bezpečnosti inteligentní domácnosti." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2018. http://www.nusl.cz/ntk/nusl-378362.

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This diploma thesis is focused on increasing Smart Home Control System security in terms of information, network and physical security. It is based on a risk analysis of the current state of applied security management and the needs of the house owner. Both security countermeasure and cost analysis are thoroughly discussed, and the thesis also contains methodology, which describes the management of smart home security and improvement of end-user security awareness.
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Shelton, Madura Anushanga. "Towards Automatic Power Analysis Leakage Elimination." Thesis, 2022. https://hdl.handle.net/2440/136025.

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Side channel attacks were first described on timing based information leakage in 1996 by Paul Kocher. Similar leakage can also be observed through physical properties such as electro-magnetic emanations, acoustics and power consumption. Masking is a countermeasure that splits sensitive values into separate values called shares. However, due to the existence of unintended interactions in hardware, masked implementations may fail to reach their advertised security level. We propose an emulation based approach to find and eliminate leakage caused by unintended interactions. This thesis presents three main contributions, ELMO*, Rosita and Rosita++. ELMO* is a modified version of ELMO (McCann et al. USENIX Security 2017) which can emulate leakage from unintended interactions realistically. Rosita and Rosita++ are two code rewriting tools that can fix univariate and multivariate leakage by using emulated leakage from ELMO*. We tested Rosita on first-order masked implementations of AES, ChaCha and Xoodoo and the slowdown incurred by the fixes were 21.3%, 75% and 32.3%. Rosita eliminated more than 90% of all observed leakage on a STM32F030 Discovery Evaluation board. We evaluated Rosita++ on second-order masked implementations of Boolean-to-arithmetic masking, PRESENT and Xoodoo where it eliminated all leakage in Boolean-to-arithmetic and Xoodoo implementations. The slowdown incurred by fixes applied were 36%, 29% and 189%. It was also evaluated on a third-order masked synthetic example using 30 million power traces recorded from the target device, where Rosita++ fixed all detected leakage. Our contributions have been presented at NDSS 2021 and CCS 2021 conferences.
Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 2022
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Ali, Bako. "Internet of Things based Smart Homes : Security Risk Assessment and Recommendations." Thesis, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-58806.

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The Internet of Things (IoT) is an emerging paradigm focusing on the inter-connection of things or devices to each other and to the users. Over time, the most of connections in IoT are shifting from ‘Human to Thing’ to ‘Thing to Thing’. This technology is anticipated to become an essential milestone in the development of smart homes to bring convenience and efficiency into our lives and our homes. But, by bringing this IoT technology into our homes there will be important implications for security in these technologies. Connecting every smart objects inside the home to the internet and to each other results in new security and privacy problems, e.g., confidentiality, authenticity, and integrity of data sensed and exchanged by objects. These technologies are very much vulnerable to different security attacks that make an IoT-based smart home unsecure to live in and therefore it is necessary to evaluate the security risks to judge the situation of the smart homes. For any technology to be successful and achieve widespread use, it needs to gain the trust of users by providing sufficient security and privacy assurance. As in all sectors, maintaining security will be a critical challenge to overcome. As homes are increasingly computerized and filled with devices, potential computer security attacks and their impact on residents need to be investigated. This report uses OCTAVE Allegro Methodology which focuses mainly on information assets and considers containers (technical, physical and people) and conducts a security risk assessment with the goal of highlighting various security flaws in IoT-based smart home, impacts and proposing countermeasures to the identified issues satisfying most of security requirements. Finally, it comes up with some recommendations to the users. The research findings documented into a thesis paper for secure IoT-based smart home systems and the resulted list and recommendations will be some useful contribution which can be used as a foundation for the specification of security requirements. For future work, the assessment will be extended to include more types of smart home applications rather than just typical one.

Validerat; 20160620 (global_studentproject_submitter)

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Books on the topic "Automatic countermeasures"

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Wassim, Najm, and John A. Volpe National Transportation Systems Center (U.S.), eds. Synthesis report: Examination of target vehicular crashes and potential ITS countermeasures. [Washington, D.C.]: National Highway Traffic Safety Administration, 1995.

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Neudert, Lisa-Maria N. Germany. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190931407.003.0008.

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As concerns over misinformation, political bots, and the impact of social media on public discourse manifest in Germany, this chapter explores the role of computational propaganda in and around German politics. The research sheds light on how algorithms, automation, and big data are leveraged to manipulate the German public, presenting real-time social media data and rich evidence from interviews with a wide range of German Internet experts—bot developers, policymakers, cyberwarfare specialists, victims of automated attacks, and social media moderators. In addition, the chapter examines how the ongoing public debate surrounding the threats of right-wing political currents and foreign election interference in the Federal Election 2017 has created sentiments of concern and fear. Imposed regulation, multi-stakeholder actionism, and sustained media attention remain unsubstantiated by empirical findings of computational propaganda. The chapter provides an in-depth analysis of social media discourse during the German parliamentary election 2016. Pioneering the methodological assessment of the magnitude of automation and junk news, the author finds limited evidence of computational propaganda in Germany. The author concludes that the impact of computational propaganda, nonetheless, is substantial in Germany, promoting a dispersed civic debate, political vigilance, and restrictive countermeasures that leave a deep imprint on the freedom and openness of the public discourse in Germany.
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Book chapters on the topic "Automatic countermeasures"

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Belleville, Nicolas, Karine Heydemann, Damien Couroussé, Thierno Barry, Bruno Robisson, Abderrahmane Seriai, and Henri-Pierre Charles. "Automatic Application of Software Countermeasures Against Physical Attacks." In Cyber-Physical Systems Security, 135–55. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98935-8_7.

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Breier, Jakub, and Xiaolu Hou. "Automated Deployment of Software Encoding Countermeasure." In Automated Methods in Cryptographic Fault Analysis, 173–94. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11333-9_7.

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Bayrak, Ali Galip, Francesco Regazzoni, David Novo, and Paolo Ienne. "Sleuth: Automated Verification of Software Power Analysis Countermeasures." In Cryptographic Hardware and Embedded Systems - CHES 2013, 293–310. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40349-1_17.

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Schmidt, Henrik, and Joseph R. Edwards. "Goats: Multi-Platform Sonar Concept for Coastal Mine Countermeasures." In Multi-Robot Systems: From Swarms to Intelligent Automata, 133–40. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-017-2376-3_14.

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Regan, Michael A., and Oscar Oviedo-Trespalacios. "Driver Distraction: Mechanisms, Evidence, Prevention, and Mitigation." In The Vision Zero Handbook, 1–62. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-23176-7_38-1.

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AbstractIn this chapter, the reader is introduced to the topic of driver distraction: its definition and mechanisms; its impact on driving performance and safety; approaches to preventing it; evidence-based injury prevention and mitigation countermeasures; and new frames of reference for conceptualizing distraction as traditional driving functions and tasks become increasingly automated. Some strategies that might be considered by societal stakeholders in setting a coordinated agenda for the management of distracted driving going into the future are also presented. Until all vehicles can safely drive themselves, in all conditions, all of the time, it is unlikely that, for driver distraction, Vision Zero will be achieved. In the meantime, however, there is much that can be done to slow its spread and mitigate it effects.
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Regan, Michael A., and Oscar Oviedo-Trespalacios. "Driver Distraction: Mechanisms, Evidence, Prevention, and Mitigation." In The Vision Zero Handbook, 995–1056. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-76505-7_38.

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AbstractIn this chapter, the reader is introduced to the topic of driver distraction: its definition and mechanisms; its impact on driving performance and safety; approaches to preventing it; evidence-based injury prevention and mitigation countermeasures; and new frames of reference for conceptualizing distraction as traditional driving functions and tasks become increasingly automated. Some strategies that might be considered by societal stakeholders in setting a coordinated agenda for the management of distracted driving going into the future are also presented. Until all vehicles can safely drive themselves, in all conditions, all of the time, it is unlikely that, for driver distraction, Vision Zero will be achieved. In the meantime, however, there is much that can be done to slow its spread and mitigate it effects.
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Karmakar, Sandip, and Dipanwita Roy Chowdhury. "Countermeasures of Side Channel Attacks on Symmetric Key Ciphers Using Cellular Automata." In Lecture Notes in Computer Science, 623–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33350-7_64.

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Zhong, Xiao Feng, De Chang Liu, Ping Luo, and Hai Yi Zhou. "Fault Diagnosis and Countermeasure for the Pantograph Automatic Lowering Under the Condition of Dual-Locomotive Running." In Lecture Notes in Electrical Engineering, 429–35. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7989-4_43.

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Nguyen, Hai Thanh, Katrin Franke, and Slobodan Petrovic. "Feature Extraction Methods for Intrusion Detection Systems." In Threats, Countermeasures, and Advances in Applied Information Security, 23–52. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0978-5.ch002.

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Intrusion Detection Systems (IDSs) have become an important security tool for managing risk and an indispensable part of overall security architecture. An IDS is considered as a pattern recognition system, in which feature extraction is an important pre-processing step. The feature extraction process consists of feature construction and feature selection . The quality of the feature construction and feature selection algorithms is one of the most important factors that affects the effectiveness of an IDS. Achieving reduction of the number of relevant traffic features without negative effect on classification accuracy is a goal that largely improves the overall effectiveness of the IDS. Most of the feature construction as well as feature selection works in intrusion detection practice is still carried through manually by utilizing domain knowledge. For automatic feature construction and feature selection, the filter, wrapper, and embedded methods from machine learning are frequently applied. This chapter provides an overview of various existing feature construction and feature selection methods for intrusion detection systems. A comparison between those feature selection methods is performed in the experimental part.
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Al-Saadoon, Ghossoon M. Waleed. "Automatic Intrusion Detection and Secret Multi Agent Preservation Using Authentication Measurement Network Threat." In Handbook of Research on Threat Detection and Countermeasures in Network Security, 33–47. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-6583-5.ch003.

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The computer sciences and their applications are developing continuously. This growth should be protected. One of the methods to fulfill this approach by using the encryption method ‘Rijndael Advanced Encryption Standard' is applied for security information DBs, to prevent an unauthorized user from accessing any stored information. The security method determines the resources that agents are able to have an access and to give permission to other agents. Security and security assurance are special integrity in agent system to enable it to cooperate or to complete the application and where agent system may not be trustful to visiting agents. Ideas of this chapter of using multi agent framework is to design the proposed Automatic Intrusion Detection model and to secret multi agent preservation using authentication measurement network threat. This approach uses statistical models to correlate and analyse data in the network. It takes the decisions to control both local and global agent's data bases perceptively. Also it adopts the security problem authentication and authorization by providing a secure distributed agent system.
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Conference papers on the topic "Automatic countermeasures"

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Sere, Ahmadou A., Julien Iguchi-Cartigny, and Jean-Louis Lanet. "Automatic detection of fault attack and countermeasures." In the 4th Workshop. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1631716.1631723.

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Evans, Nicholas, Tomi Kinnunen, and Junichi Yamagishi. "Spoofing and countermeasures for automatic speaker verification." In Interspeech 2013. ISCA: ISCA, 2013. http://dx.doi.org/10.21437/interspeech.2013-288.

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Alluri, K. N. R. K. Raju, and Anil Kumar Vuppala. "IIIT-H Spoofing Countermeasures for Automatic Speaker Verification Spoofing and Countermeasures Challenge 2019." In Interspeech 2019. ISCA: ISCA, 2019. http://dx.doi.org/10.21437/interspeech.2019-1623.

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Liu, Songxiang, Haibin Wu, Hung-Yi Lee, and Helen Meng. "Adversarial Attacks on Spoofing Countermeasures of Automatic Speaker Verification." In 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU). IEEE, 2019. http://dx.doi.org/10.1109/asru46091.2019.9003763.

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Alegre, Federico, Asmaa Amehraye, and Nicholas Evans. "Spoofing countermeasures to protect automatic speaker verification from voice conversion." In ICASSP 2013 - 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2013. http://dx.doi.org/10.1109/icassp.2013.6638222.

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Bayrak, Ali Galip, Francesco Regazzoni, Philip Brisk, François-Xavier Standaert, and Paolo Ienne. "A first step towards automatic application of power analysis countermeasures." In the 48th Design Automation Conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2024724.2024778.

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Wu, Zhizheng, Tomi Kinnunen, Nicholas Evans, Junichi Yamagishi, Cemal Hanilçi, Md Sahidullah, and Aleksandr Sizov. "ASVspoof 2015: the first automatic speaker verification spoofing and countermeasures challenge." In Interspeech 2015. ISCA: ISCA, 2015. http://dx.doi.org/10.21437/interspeech.2015-462.

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Bhukya, Ramesh K., and Aditya Raj. "Automatic Speaker Verification Spoof Detection and Countermeasures Using Gaussian Mixture Model." In 2022 IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON). IEEE, 2022. http://dx.doi.org/10.1109/upcon56432.2022.9986418.

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Sahidullah, Md, Héctor Delgado, Massimiliano Todisco, Hong Yu, Tomi Kinnunen, Nicholas Evans, and Zheng-Hua Tan. "Integrated Spoofing Countermeasures and Automatic Speaker Verification: An Evaluation on ASVspoof 2015." In Interspeech 2016. ISCA, 2016. http://dx.doi.org/10.21437/interspeech.2016-1280.

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Kang, Woo Hyun, Jahangir Alam, and Abderrahim Fathan. "CRIM's System Description for the ASVSpoof2021 Challenge." In 2021 Edition of the Automatic Speaker Verification and Spoofing Countermeasures Challenge. ISCA: ISCA, 2021. http://dx.doi.org/10.21437/asvspoof.2021-16.

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Reports on the topic "Automatic countermeasures"

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Hu, Xiaoqiang, Jieyi Bao, Yi Jiang, and Shuo Li. Highway Lighting Test Bed on INDOT Facility (Off-Roadway). Purdue University, 2022. http://dx.doi.org/10.5703/1288284317384.

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According to the National Highway Traffic Safety Administration (NHTSA), during 2016 there were 7,277,000 vehicle crashes nationally. Among them, approximately 70% happened during the daytime and around 30% of crashes occurred during the nighttime. There were 11,375 nighttime fatal crashes that account for about 48% of total fatal crashes (23,714). Given the fact that only 25%–33% of the vehicle miles traveled (VMT) occur at night, the above statistics indicate that the nighttime crash fatality rate is much higher and nighttime crashes are usually more severe compared to daytime crashes. Providing lighting on roadways is one of the proven safety countermeasures for preventing crashes and reducing fatalities. In particular, lighting at roadway intersections can reduce vehicle crashes by 10% to 26%. Currently, to conduct lighting field testing, INDOT is using several in-service highways, intersections, interchanges, and rest areas. These locations require traffic control and lane closures, which raises safety concerns and causing inconvenience to the public. In addition to the cost and safety concerns, during the evaluation period the new luminaires being tested actually functioned as lighting sources in place of the existing luminaires that were removed in order to install the new luminaires. This means that the new luminaries were used for roadway lighting at the test sites even before they were proven to meet the roadway lighting requirements. To eliminate traffic control and potential safety concerns, it was proposed to create test beds for field evaluating and to verify the performance of new lighting technologies and luminaires in a controlled, standard setting. Through this study, two lighting test bed facilities were designed and constructed. Illuminance values of installed luminaires were manually measured by a remotely controlled electric cart and drone. The measured illuminance values were analyzed and the analysis indicated that the efficiency of illuminance measurement can be significantly improved by automated methods. An illuminance data repository model was developed to be an effective tool that can greatly facilitate data input and storage process. The use of this model will further increase the productivity of illuminance measurement at the lighting test beds.
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