Cyber-physical systems operate in our real world, constantly interacting with the environment and collaborating with other systems. The increasing number of devices will make it infeasible to control each one individually. It will also be infeasible to prepare each of them for every imaginable rapidly unfolding situation. Therefore, we must increase the autonomy of future Cyber-physical Systems. Making these systems self-aware allows them to reason about their own capabilities and their immediate environment. In this article, we extend the idea of the self-awareness of individual systems toward networked self-awareness. This gives systems the ability to reason about how they are being affected by the actions and interactions of others within their perceived environment, as well as in the extended environment that is beyond their direct perception. We propose that different levels of networked self-awareness can develop over time in systems as they do in humans. Furthermore, we propose that this could have the same benefits for networks of systems that it has had for communities of humans, increasing performance and adaptability.
{"title":"I Think Therefore You Are","authors":"Lukas Esterle, John N. A. Brown","doi":"10.1145/3375403","DOIUrl":"https://doi.org/10.1145/3375403","url":null,"abstract":"Cyber-physical systems operate in our real world, constantly interacting with the environment and collaborating with other systems. The increasing number of devices will make it infeasible to control each one individually. It will also be infeasible to prepare each of them for every imaginable rapidly unfolding situation. Therefore, we must increase the autonomy of future Cyber-physical Systems. Making these systems self-aware allows them to reason about their own capabilities and their immediate environment. In this article, we extend the idea of the self-awareness of individual systems toward networked self-awareness. This gives systems the ability to reason about how they are being affected by the actions and interactions of others within their perceived environment, as well as in the extended environment that is beyond their direct perception. We propose that different levels of networked self-awareness can develop over time in systems as they do in humans. Furthermore, we propose that this could have the same benefits for networks of systems that it has had for communities of humans, increasing performance and adaptability.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":" ","pages":"1 - 25"},"PeriodicalIF":2.3,"publicationDate":"2020-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3375403","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48287201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yunhao Bai, Kuangyu Zheng, Zejiang Wang, Xiaorui Wang, Junmin Wang
In a Vehicular Cyber Physical System (VCPS), ensuring the real-time delivery of safety messages is an important research problem for Vehicle to Vehicle (V2V) communication. Unfortunately, existing work relies only on one or two pre-selected control channels for safety message communication, which can result in poor packet delivery and potential accident when the vehicle density is high. If all the available channels can be dynamically utilized when the control channel is having severe contention, then safety messages can have a much better chance to meet their real-time deadlines. In this article, we propose MC-Safe, a multi-channel V2V communication framework that monitors all the available channels and dynamically selects the best one for safety message transmission. During normal driving, MC-Safe monitors periodic beacons sent by other vehicles and estimates the communication delay on all the channels. Upon the detection of a potential accident, MC-Safe leverages a novel channel negotiation scheme that allows all the involved vehicles to work collaboratively, in a distributed manner, for identifying a communication channel that meets the delay requirement. MC-safe also features a novel coordinator selection algorithm that minimizes the delay of channel negotiation. Once a channel is selected, all the involved vehicles switch to the same selected channel for real-time communication with the least amount of interference. Our evaluation results both in simulation and on a hardware testbed with scaled cars show that MC-Safe outperforms existing single-channel solutions and other well-designed multi-channel baselines by having a 23.4% lower packet delay on average compared with other well-designed channel selection baselines.
{"title":"MC-Safe","authors":"Yunhao Bai, Kuangyu Zheng, Zejiang Wang, Xiaorui Wang, Junmin Wang","doi":"10.1145/3394961","DOIUrl":"https://doi.org/10.1145/3394961","url":null,"abstract":"In a Vehicular Cyber Physical System (VCPS), ensuring the real-time delivery of safety messages is an important research problem for Vehicle to Vehicle (V2V) communication. Unfortunately, existing work relies only on one or two pre-selected control channels for safety message communication, which can result in poor packet delivery and potential accident when the vehicle density is high. If all the available channels can be dynamically utilized when the control channel is having severe contention, then safety messages can have a much better chance to meet their real-time deadlines. In this article, we propose MC-Safe, a multi-channel V2V communication framework that monitors all the available channels and dynamically selects the best one for safety message transmission. During normal driving, MC-Safe monitors periodic beacons sent by other vehicles and estimates the communication delay on all the channels. Upon the detection of a potential accident, MC-Safe leverages a novel channel negotiation scheme that allows all the involved vehicles to work collaboratively, in a distributed manner, for identifying a communication channel that meets the delay requirement. MC-safe also features a novel coordinator selection algorithm that minimizes the delay of channel negotiation. Once a channel is selected, all the involved vehicles switch to the same selected channel for real-time communication with the least amount of interference. Our evaluation results both in simulation and on a hardware testbed with scaled cars show that MC-Safe outperforms existing single-channel solutions and other well-designed multi-channel baselines by having a 23.4% lower packet delay on average compared with other well-designed channel selection baselines.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":" ","pages":"1 - 27"},"PeriodicalIF":2.3,"publicationDate":"2020-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3394961","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47495010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Matthew Weber, Baihong Jin, Gil Lederman, Yasser Shoukry, Edward A. Lee, S. Seshia, A. Sangiovanni-Vincentelli
Accurate localization from Cyber-Physical Systems (CPS) is a critical enabling technology for context-aware applications and control. As localization plays an increasingly safety-critical role, location systems must be able to identify and eliminate faulty measurements to prevent dangerously inaccurate localization. In this article, we consider the range-based localization problem and propose a method to detect coordinated adversarial corruption on anchor positions and distance measurements. Our algorithm, Gordian, rapidly finds attacks by identifying geometric inconsistencies at the graph level without requiring assumptions about hardware, ranging mechanisms, or cryptographic protocols. We give necessary conditions for which attack detection is guaranteed to be successful in the noiseless case, and we use that intuition to extend Gordian to the noisy case where fewer guarantees are possible. In simulations generated from real-world sensor noise, we empirically show that Gordian’s trilateration counterexample generation procedure enables rapid attack detection even for combinatorially difficult problems.
{"title":"Gordian","authors":"Matthew Weber, Baihong Jin, Gil Lederman, Yasser Shoukry, Edward A. Lee, S. Seshia, A. Sangiovanni-Vincentelli","doi":"10.1145/3386568","DOIUrl":"https://doi.org/10.1145/3386568","url":null,"abstract":"Accurate localization from Cyber-Physical Systems (CPS) is a critical enabling technology for context-aware applications and control. As localization plays an increasingly safety-critical role, location systems must be able to identify and eliminate faulty measurements to prevent dangerously inaccurate localization. In this article, we consider the range-based localization problem and propose a method to detect coordinated adversarial corruption on anchor positions and distance measurements. Our algorithm, Gordian, rapidly finds attacks by identifying geometric inconsistencies at the graph level without requiring assumptions about hardware, ranging mechanisms, or cryptographic protocols. We give necessary conditions for which attack detection is guaranteed to be successful in the noiseless case, and we use that intuition to extend Gordian to the noisy case where fewer guarantees are possible. In simulations generated from real-world sensor noise, we empirically show that Gordian’s trilateration counterexample generation procedure enables rapid attack detection even for combinatorially difficult problems.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":"15 1","pages":"1 - 27"},"PeriodicalIF":2.3,"publicationDate":"2020-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89094125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Markov Decision Processes (MDPs) provide important capabilities for facilitating the dynamic adaptation and self-optimization of cyber physical systems at runtime. In recent years, this has primarily taken the form of Reinforcement Learning (RL) techniques that eliminate some MDP components for the purpose of reducing computational requirements. In this work, we show that recent advancements in Compact MDP Models (CMMs) provide sufficient cause to question this trend when designing wireless sensor network nodes. In this work, a novel CMM-based approach to designing self-aware wireless sensor nodes is presented and compared to Q-Learning, a popular RL technique. We show that a certain class of CPS nodes is not well served by RL methods and contrast RL versus CMM methods in this context. Through both simulation and a prototype implementation, we demonstrate that CMM methods can provide significantly better runtime adaptation performance relative to Q-Learning, with comparable resource requirements.
{"title":"Runtime Adaptation in Wireless Sensor Nodes Using Structured Learning","authors":"A. Sapio, S. Bhattacharyya, M. Wolf","doi":"10.1145/3372153","DOIUrl":"https://doi.org/10.1145/3372153","url":null,"abstract":"Markov Decision Processes (MDPs) provide important capabilities for facilitating the dynamic adaptation and self-optimization of cyber physical systems at runtime. In recent years, this has primarily taken the form of Reinforcement Learning (RL) techniques that eliminate some MDP components for the purpose of reducing computational requirements. In this work, we show that recent advancements in Compact MDP Models (CMMs) provide sufficient cause to question this trend when designing wireless sensor network nodes. In this work, a novel CMM-based approach to designing self-aware wireless sensor nodes is presented and compared to Q-Learning, a popular RL technique. We show that a certain class of CPS nodes is not well served by RL methods and contrast RL versus CMM methods in this context. Through both simulation and a prototype implementation, we demonstrate that CMM methods can provide significantly better runtime adaptation performance relative to Q-Learning, with comparable resource requirements.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":"4 1","pages":"1 - 28"},"PeriodicalIF":2.3,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3372153","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48069251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The lack of any sender authentication mechanism in place makes Controller Area Network (CAN) vulnerable to security threats. For instance, an attacker can impersonate an Electronic Control Unit (ECU) on the bus and send spoofed messages unobtrusively with the identifier of the impersonated ECU. To address this problem, we propose a novel source authentication technique that uses power consumption measurements of the ECU to authenticate the source of a message. A transmission of an ECU affects the power consumption and a characteristic pattern will appear. Our technique exploits the power consumption of each ECU during the transmission of a message to determine whether the message actually originated from the purported sender. We evaluate our approach in both a lab setup and a real vehicle. We also evaluate our approach against factors that can impact the power consumption measurement of the ECU. The results of the evaluation show that the proposed technique is applicable in a broad range of operating conditions with reasonable computational power requirements and attaining good accuracy.
{"title":"CANOA: CAN Origin Authentication Through Power Side-Channel Monitoring","authors":"Shailja Thakur, Carlos Moreno, S. Fischmeister","doi":"10.1145/3571288","DOIUrl":"https://doi.org/10.1145/3571288","url":null,"abstract":"The lack of any sender authentication mechanism in place makes Controller Area Network (CAN) vulnerable to security threats. For instance, an attacker can impersonate an Electronic Control Unit (ECU) on the bus and send spoofed messages unobtrusively with the identifier of the impersonated ECU. To address this problem, we propose a novel source authentication technique that uses power consumption measurements of the ECU to authenticate the source of a message. A transmission of an ECU affects the power consumption and a characteristic pattern will appear. Our technique exploits the power consumption of each ECU during the transmission of a message to determine whether the message actually originated from the purported sender. We evaluate our approach in both a lab setup and a real vehicle. We also evaluate our approach against factors that can impact the power consumption measurement of the ECU. The results of the evaluation show that the proposed technique is applicable in a broad range of operating conditions with reasonable computational power requirements and attaining good accuracy.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2020-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49519523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ke Huang, Xiaosong Zhang, Xiaofeng Wang, Y. Mu, F. Rezaeibagha, Guangquan Xu, Hao Wang, Xi Zheng, Guomin Yang, Qi Xia, Xiaojiang Du
Outsourcing helps relocate data from the cyber-physical system (CPS) for efficient storage at low cost. Current server-based outsourcing mainly focuses on the benefits of servers. This cannot attract users well, as their security, efficiency, and economy are not guaranteed. To solve with this issue, a hybrid outsourcing model that exploits both cloud server and edge devices to store data is needed. Meanwhile, the requirements of security and efficiency are different under specific scenarios. There is a lack of a comprehensive solution that considers all of the above issues. In this work, we overcome the above issues by proposing the first hybrid user-centric data outsourcing (HUCDO) scheme. It allows users to outsource data securely, efficiently, and economically via different CPSs. Brielly, our contributions consist of theories, implementations, and evaluations. Our theories include the first homomorphic collision-resistant chameleon hash (HCCH) and homomorphic designated-receiver signcryption (HDRS). As implementations, we instantiate how to use our proposals to outsource small- or large-scale data through distinct CPS, respectively. Additionally, a blockchain with proof-of-discrete-logarithm (B-PoDL) is instantiated to help improve our performance. Last, as demonstrated by our evaluations, our proposals are secure, efficient, and economic for users to implement while outsourcing their data via CPSs.
{"title":"HUCDO: A Hybrid User-centric Data Outsourcing Scheme","authors":"Ke Huang, Xiaosong Zhang, Xiaofeng Wang, Y. Mu, F. Rezaeibagha, Guangquan Xu, Hao Wang, Xi Zheng, Guomin Yang, Qi Xia, Xiaojiang Du","doi":"10.1145/3379464","DOIUrl":"https://doi.org/10.1145/3379464","url":null,"abstract":"Outsourcing helps relocate data from the cyber-physical system (CPS) for efficient storage at low cost. Current server-based outsourcing mainly focuses on the benefits of servers. This cannot attract users well, as their security, efficiency, and economy are not guaranteed. To solve with this issue, a hybrid outsourcing model that exploits both cloud server and edge devices to store data is needed. Meanwhile, the requirements of security and efficiency are different under specific scenarios. There is a lack of a comprehensive solution that considers all of the above issues. In this work, we overcome the above issues by proposing the first hybrid user-centric data outsourcing (HUCDO) scheme. It allows users to outsource data securely, efficiently, and economically via different CPSs. Brielly, our contributions consist of theories, implementations, and evaluations. Our theories include the first homomorphic collision-resistant chameleon hash (HCCH) and homomorphic designated-receiver signcryption (HDRS). As implementations, we instantiate how to use our proposals to outsource small- or large-scale data through distinct CPS, respectively. Additionally, a blockchain with proof-of-discrete-logarithm (B-PoDL) is instantiated to help improve our performance. Last, as demonstrated by our evaluations, our proposals are secure, efficient, and economic for users to implement while outsourcing their data via CPSs.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":"4 1","pages":"35:1-35:23"},"PeriodicalIF":2.3,"publicationDate":"2020-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3379464","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64026470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Di Wu, Hanlin Zhu, Yongxin Zhu, Victor I. Chang, Cong He, Ching‐Hsien Hsu, Hui Wang, Songlin Feng, Li Tian, Zunkai Huang
Advanced Driver Assistance System (ADAS) is a typical Cyber Physical System (CPS) application for human–computer interaction. In the process of vehicle driving, we use the information from CPS on ADAS to not only help us understand the driving condition of the car but also help us change the driving strategies to drive in a better and safer way. After getting the information, the driver can evaluate the feedback information of the vehicle, so as to enhance the ability to assist in driving of the ADAS system. This completes a complete human–computer interaction process. However, the data obtained during the interaction usually form a large dimension, and irrelevant features sometimes hide the occurrence of anomalies, which poses a significant challenge to us to better understand the driving states of the car. To solve this problem, we propose an anomaly detection framework based on RBM-LSTM. In this hybrid framework, RBM is trained to extract general underlying features from data collected by CPS, and LSTM is trained from the features learned by RBM. This framework can effectively improve the prediction speed and present a good prediction accuracy to show vehicle driving condition. Besides, drivers are allowed to evaluate the prediction results, so as to improve the accuracy of prediction. Through the experimental results, we can find that the proposed framework not only simplifies the training of the entire neural network and increases the training speed but also greatly improves the accuracy of the interaction-driven data analysis. It is a valid method to analyze the data generated during the human interaction.
{"title":"Anomaly Detection Based on RBM-LSTM Neural Network for CPS in Advanced Driver Assistance System","authors":"Di Wu, Hanlin Zhu, Yongxin Zhu, Victor I. Chang, Cong He, Ching‐Hsien Hsu, Hui Wang, Songlin Feng, Li Tian, Zunkai Huang","doi":"10.1145/3377408","DOIUrl":"https://doi.org/10.1145/3377408","url":null,"abstract":"Advanced Driver Assistance System (ADAS) is a typical Cyber Physical System (CPS) application for human–computer interaction. In the process of vehicle driving, we use the information from CPS on ADAS to not only help us understand the driving condition of the car but also help us change the driving strategies to drive in a better and safer way. After getting the information, the driver can evaluate the feedback information of the vehicle, so as to enhance the ability to assist in driving of the ADAS system. This completes a complete human–computer interaction process. However, the data obtained during the interaction usually form a large dimension, and irrelevant features sometimes hide the occurrence of anomalies, which poses a significant challenge to us to better understand the driving states of the car. To solve this problem, we propose an anomaly detection framework based on RBM-LSTM. In this hybrid framework, RBM is trained to extract general underlying features from data collected by CPS, and LSTM is trained from the features learned by RBM. This framework can effectively improve the prediction speed and present a good prediction accuracy to show vehicle driving condition. Besides, drivers are allowed to evaluate the prediction results, so as to improve the accuracy of prediction. Through the experimental results, we can find that the proposed framework not only simplifies the training of the entire neural network and increases the training speed but also greatly improves the accuracy of the interaction-driven data analysis. It is a valid method to analyze the data generated during the human interaction.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":"4 1","pages":"1 - 17"},"PeriodicalIF":2.3,"publicationDate":"2020-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3377408","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42822244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Saxena, A. Cárdenas, R. Beyah, R. Lu, K. Choo, Yiran Chen
The recent spate of cyber security attacks has reinforced the importance of cyber security. Cyber security is no longer just a technical issue requiring the proficiency and capabilities of technical experts, it is a global phenomenon requiring the attention of stakeholders across different information domains. We organize this special issue on user-centric security and safety aspects of cyber-physical systems (CPS) with the aim of filling gaps between user behaviour and the design of complex CPS. These include different stakeholders’ roles and responsibilities, user-centric decision-making capabilities and situational awareness, user experience design, mitigation of user errors and analysing their impact, adaptive risk management, user or operator’s trust, security and safety in the device’s or system’s authentication, access control, and configuration management, hence, the relation to the development of the system’s security and safety in the cyber-physical world. It is presumed that alignment of user-oriented processes, standards, and guidelines for security and safety are required to cope with the complexities and interoperability of cyber-physical systems. In other words, this special issue aims to publish the latest advancements in user-centric security and safety techniques and controls for CPS and related components. The following seven contributed articles are included in this special issue: The first article, entitled “Efficient Multi-factor User Authentication Protocol with Forward Secrecy for Real-time Data Access in WSNs,” proposes a robust multi-factor authentication scheme that makes use of the imbalanced computational nature of the RSA cryptosystem, particularly suitable for scenarios where sensor nodes (but not the user’s device) are the main energy bottleneck. This work is the first one that can satisfy all 12 criteria of the state-of-the-art evaluation metric under the harshest adversary model so far. The second article, entitled “A Multi-label Fuzzy Relevance Clustering System for Malware Attack Attribution in the Edge Layer of Cyber Physical Networks,” proposes a novel multi-label fuzzy clustering system for malware attack attribution. The authors first observed that a multilabel classifier does not classify a part of the samples when classifying malware families. To overcome this problem, the authors developed an ensemble-based multi-label fuzzy classification method to suggest the relevance of a malware instance to the stricken families. The third article, entitled “A User-centric Security Solution for Internet of Things and Edge Convergence,” proposes a user-centric security solution to ensure the trustworthiness of the data for emergency evaluation in Edge datacenters (EDCs). A user centric security approach by authenticating users and devices before any communications is established. The fourth article, entitled “MobileTrust: Secure Knowledge Integration in VANETs,” is about the security of Vehicular Ad hoc NETworks (VAN
{"title":"Introduction to the Special Issue on User-Centric Security and Safety for CPS","authors":"N. Saxena, A. Cárdenas, R. Beyah, R. Lu, K. Choo, Yiran Chen","doi":"10.1145/3392715","DOIUrl":"https://doi.org/10.1145/3392715","url":null,"abstract":"The recent spate of cyber security attacks has reinforced the importance of cyber security. Cyber security is no longer just a technical issue requiring the proficiency and capabilities of technical experts, it is a global phenomenon requiring the attention of stakeholders across different information domains. We organize this special issue on user-centric security and safety aspects of cyber-physical systems (CPS) with the aim of filling gaps between user behaviour and the design of complex CPS. These include different stakeholders’ roles and responsibilities, user-centric decision-making capabilities and situational awareness, user experience design, mitigation of user errors and analysing their impact, adaptive risk management, user or operator’s trust, security and safety in the device’s or system’s authentication, access control, and configuration management, hence, the relation to the development of the system’s security and safety in the cyber-physical world. It is presumed that alignment of user-oriented processes, standards, and guidelines for security and safety are required to cope with the complexities and interoperability of cyber-physical systems. In other words, this special issue aims to publish the latest advancements in user-centric security and safety techniques and controls for CPS and related components. The following seven contributed articles are included in this special issue: The first article, entitled “Efficient Multi-factor User Authentication Protocol with Forward Secrecy for Real-time Data Access in WSNs,” proposes a robust multi-factor authentication scheme that makes use of the imbalanced computational nature of the RSA cryptosystem, particularly suitable for scenarios where sensor nodes (but not the user’s device) are the main energy bottleneck. This work is the first one that can satisfy all 12 criteria of the state-of-the-art evaluation metric under the harshest adversary model so far. The second article, entitled “A Multi-label Fuzzy Relevance Clustering System for Malware Attack Attribution in the Edge Layer of Cyber Physical Networks,” proposes a novel multi-label fuzzy clustering system for malware attack attribution. The authors first observed that a multilabel classifier does not classify a part of the samples when classifying malware families. To overcome this problem, the authors developed an ensemble-based multi-label fuzzy classification method to suggest the relevance of a malware instance to the stricken families. The third article, entitled “A User-centric Security Solution for Internet of Things and Edge Convergence,” proposes a user-centric security solution to ensure the trustworthiness of the data for emergency evaluation in Edge datacenters (EDCs). A user centric security approach by authenticating users and devices before any communications is established. The fourth article, entitled “MobileTrust: Secure Knowledge Integration in VANETs,” is about the security of Vehicular Ad hoc NETworks (VAN","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":"4 1","pages":"1 - 2"},"PeriodicalIF":2.3,"publicationDate":"2020-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3392715","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43476845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PuthalDeepak, T. YangLaurence, DustdarSchahram, WenZhenyu, JunSong, MoorselAad van, RanjanRajiv
The Internet of Things (IoT) is becoming a backbone of sensing infrastructure to several mission-critical applications such as smart health, disaster management, and smart cities. Due to resource-c...
{"title":"A User-centric Security Solution for Internet of Things and Edge Convergence","authors":"PuthalDeepak, T. YangLaurence, DustdarSchahram, WenZhenyu, JunSong, MoorselAad van, RanjanRajiv","doi":"10.1145/3351882","DOIUrl":"https://doi.org/10.1145/3351882","url":null,"abstract":"The Internet of Things (IoT) is becoming a backbone of sensing infrastructure to several mission-critical applications such as smart health, disaster management, and smart cities. Due to resource-c...","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":"4 1","pages":"1-19"},"PeriodicalIF":2.3,"publicationDate":"2020-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3351882","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45195452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kai-Björn Gemlau, Leonie Köhler, R. Ernst, Sophie Quinton
Logical Execution Time (LET) is a timed programming abstraction, which features predictable and composable timing. It has recently gained considerable attention in the automotive industry, where it was successfully applied to master the distribution of software applications on multi-core electronic control units. However, the LET abstraction in its conventional form is only valid within the scope of a single component. With the recent introduction of System-level Logical Execution Time (SL LET), the concept could be transferred to a system-wide scope. This article improves over a first paper on SL LET, by providing matured definitions and an extensive discussion of the concept. It also features a comprehensive evaluation exploring the impacts of SL LET with regard to design, verification, performance, and implementability. The evaluation goes far beyond the contexts in which LET was originally applied. Indeed, SL LET allows us to address many open challenges in the design and verification of complex embedded hardware/software systems addressing predictability, synchronization, composability, and extensibility. Furthermore, we investigate performance trade-offs, and we quantify implementation costs by providing an analysis of the additionally required buffers.
{"title":"System-level Logical Execution Time","authors":"Kai-Björn Gemlau, Leonie Köhler, R. Ernst, Sophie Quinton","doi":"10.1145/3381847","DOIUrl":"https://doi.org/10.1145/3381847","url":null,"abstract":"Logical Execution Time (LET) is a timed programming abstraction, which features predictable and composable timing. It has recently gained considerable attention in the automotive industry, where it was successfully applied to master the distribution of software applications on multi-core electronic control units. However, the LET abstraction in its conventional form is only valid within the scope of a single component. With the recent introduction of System-level Logical Execution Time (SL LET), the concept could be transferred to a system-wide scope. This article improves over a first paper on SL LET, by providing matured definitions and an extensive discussion of the concept. It also features a comprehensive evaluation exploring the impacts of SL LET with regard to design, verification, performance, and implementability. The evaluation goes far beyond the contexts in which LET was originally applied. Indeed, SL LET allows us to address many open challenges in the design and verification of complex embedded hardware/software systems addressing predictability, synchronization, composability, and extensibility. Furthermore, we investigate performance trade-offs, and we quantify implementation costs by providing an analysis of the additionally required buffers.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":" ","pages":"1 - 27"},"PeriodicalIF":2.3,"publicationDate":"2020-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3381847","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44853056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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