Reliable operation of mobile devices, such as smartphones and tablets, has become essential for a great many users around the globe. Mobile devices, however, have been reported to suffer from frequent, unexpected shutoffs - e.g., shutting off even when their batteries were shown to have up to 60% remaining state-of-charge (SoC) - especially in cold environments. Their main cause is found to be the inability of commodity mobile devices to account for the strong dependency between battery SoC and the environment temperature. To remedy this problem, we design, implement, and evaluate EA-SoC, a real-time Environment-Aware battery SoC estimation service for mobile devices. EA-SoC estimates the battery SoC with a cyber-physical approach, based on (1) a thermal circuit model in the cyber space capturing the physical interactions among the battery discharge current, temperature, and the environment, and (2) an empirically validated data-driven (i.e., cyber) model for the physical relations between battery temperature and battery resistance. We have conducted 35 experimental case-studies with two Nexus 5X smartphones to evaluate EA-SoC. EA-SoC is shown to report an average of 3% SoC when the phones shut off even in a -15°C environment, while that reported by the phones' built-in fuel-gauge chips could be over 90%.
{"title":"Environment-aware estimation of battery state-of-charge for mobile devices","authors":"Liang He, Youngmoon Lee, Eugene Kim, K. Shin","doi":"10.1145/3302509.3313782","DOIUrl":"https://doi.org/10.1145/3302509.3313782","url":null,"abstract":"Reliable operation of mobile devices, such as smartphones and tablets, has become essential for a great many users around the globe. Mobile devices, however, have been reported to suffer from frequent, unexpected shutoffs - e.g., shutting off even when their batteries were shown to have up to 60% remaining state-of-charge (SoC) - especially in cold environments. Their main cause is found to be the inability of commodity mobile devices to account for the strong dependency between battery SoC and the environment temperature. To remedy this problem, we design, implement, and evaluate EA-SoC, a real-time Environment-Aware battery SoC estimation service for mobile devices. EA-SoC estimates the battery SoC with a cyber-physical approach, based on (1) a thermal circuit model in the cyber space capturing the physical interactions among the battery discharge current, temperature, and the environment, and (2) an empirically validated data-driven (i.e., cyber) model for the physical relations between battery temperature and battery resistance. We have conducted 35 experimental case-studies with two Nexus 5X smartphones to evaluate EA-SoC. EA-SoC is shown to report an average of 3% SoC when the phones shut off even in a -15°C environment, while that reported by the phones' built-in fuel-gauge chips could be over 90%.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130299536","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}
In this work, we propose to derive realistic, accurate bounds on network-induced delays for time-critical tasks running on Avionics Full-Duplex Switched (AFDX) Ethernet. Our preliminary evaluation results show that through measurement-based modeling and refining network-calculus-based analysis with measurements tight delay bounds can be obtained for AFDX networks with realistic traffic patterns and network workloads.
{"title":"Bounding network-induced delays for time-critical services in avionic systems using measurements and network calculus","authors":"Huan Yang, Liang Cheng, Xiaoguang Ma","doi":"10.1145/3302509.3313330","DOIUrl":"https://doi.org/10.1145/3302509.3313330","url":null,"abstract":"In this work, we propose to derive realistic, accurate bounds on network-induced delays for time-critical tasks running on Avionics Full-Duplex Switched (AFDX) Ethernet. Our preliminary evaluation results show that through measurement-based modeling and refining network-calculus-based analysis with measurements tight delay bounds can be obtained for AFDX networks with realistic traffic patterns and network workloads.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131756797","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}
With the rapid development of wireless communication technologies for electrical vehicles (EVs), as a critical part of a pure EV, batteries could be attacked (e.g., draining energy) to reduce driving range and increase driving range anxiety. However, no methods have been proposed to ensure security of EV batteries. In this paper, we propose the first battery attacks, which can turn on air condition and stop battery charging process by sending requests through a smartphone without being noticed by users. We then propose a Battery authentication method (Bauth) to detect the battery attacks. We firstly build a data-driven behavior model to describe a user's habits in turning on air condition and stopping battery charging. In the behavior model, to distinguish users that share a vehicle for high modeling accuracy, we apply the random forest technology to identify each user based on battery state. Based on the established behavior model, we then build a reinforcement learning model that judges whether an AC-turn-on or batter-charge-stop request from a smartphone is from the real user based on current vehicle states. We conducted real-life daily driving experiments with different participants to evaluate the battery attack detection accuracy of Bauth. The experimental results show that Bauth can prevent EV batteries from being attacked effectively in comparison with another method and its attack detection accuracy reaches as high as 93.44%.
{"title":"Preventing battery attacks on electrical vehicles based on data-driven behavior modeling","authors":"Liuwang Kang, Haiying Shen","doi":"10.1145/3302509.3311035","DOIUrl":"https://doi.org/10.1145/3302509.3311035","url":null,"abstract":"With the rapid development of wireless communication technologies for electrical vehicles (EVs), as a critical part of a pure EV, batteries could be attacked (e.g., draining energy) to reduce driving range and increase driving range anxiety. However, no methods have been proposed to ensure security of EV batteries. In this paper, we propose the first battery attacks, which can turn on air condition and stop battery charging process by sending requests through a smartphone without being noticed by users. We then propose a Battery authentication method (Bauth) to detect the battery attacks. We firstly build a data-driven behavior model to describe a user's habits in turning on air condition and stopping battery charging. In the behavior model, to distinguish users that share a vehicle for high modeling accuracy, we apply the random forest technology to identify each user based on battery state. Based on the established behavior model, we then build a reinforcement learning model that judges whether an AC-turn-on or batter-charge-stop request from a smartphone is from the real user based on current vehicle states. We conducted real-life daily driving experiments with different participants to evaluate the battery attack detection accuracy of Bauth. The experimental results show that Bauth can prevent EV batteries from being attacked effectively in comparison with another method and its attack detection accuracy reaches as high as 93.44%.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"303 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123187843","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}
Many organizations continue to have reusable systems because they are cheaper, and associated with less time to market. Moreover, the practitioners experience lower risk if they choose to continually improve the reusable system rather than building a new system from scratch. Many reusable cyber-physical system (CPS) exist which interact with multiple physical entities. Users today expect modern CPS to satisfy a wide range of constraints at runtime. This paper characterizes the reusable CPS software by identifying the functional behaviors of the CPS as features along with the hierarchical relationships among them. We also recover dependencies (mandatory, optional, or, alternative) and cross-tree constraints (require, exclude) among the features as well as identify possible valid feature-configurations. In the experimental analysis, we discuss features and their configurations for three existing CPS software. Our framework benefits the practitioners in all stages of abstraction such as design, development, and testing.
{"title":"Feature characterization for CPS software reuse","authors":"Nayreet Islam, Akramul Azim","doi":"10.1145/3302509.3313318","DOIUrl":"https://doi.org/10.1145/3302509.3313318","url":null,"abstract":"Many organizations continue to have reusable systems because they are cheaper, and associated with less time to market. Moreover, the practitioners experience lower risk if they choose to continually improve the reusable system rather than building a new system from scratch. Many reusable cyber-physical system (CPS) exist which interact with multiple physical entities. Users today expect modern CPS to satisfy a wide range of constraints at runtime. This paper characterizes the reusable CPS software by identifying the functional behaviors of the CPS as features along with the hierarchical relationships among them. We also recover dependencies (mandatory, optional, or, alternative) and cross-tree constraints (require, exclude) among the features as well as identify possible valid feature-configurations. In the experimental analysis, we discuss features and their configurations for three existing CPS software. Our framework benefits the practitioners in all stages of abstraction such as design, development, and testing.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128073785","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}
In this paper, we propose a technique that attempts to control energy consumption in distributed cyber-physical systems (CPS) in order to improve the level of security of the system. This is in contrast to most existing methods, where the system is set to use a certain level of authentication at design time, such as basic authentication, certificate-based authentication, or no authentication at all. To this end, we propose a notion of authenticatable task graph, which encodes standard task dependencies and allows for authentication tasks to be intermittently inserted into the computation task graph. The optimization objective here is to maximize the number of authentication tasks as well as peer-authentication, while remaining in the system energy bounds. We propose three offline optimization techniques and one online algorithm, where the system can dynamically manage the tradeoff between energy consumption and the level of security in the presence of uncertainties imposed by the physical environment. Our optimization algorithms are validated by a rich set of simulations as well as a real-world case study on a group of unmanned aerial vehicles (UAVs) that are assigned area search tasks and are required to perform peer-authentication within their battery limits.
{"title":"Managing the security-energy tradeoff in distributed cyber-physical systems","authors":"Anh-Duy Vu, R. Medhat, Borzoo Bonakdarpour","doi":"10.1145/3302509.3311051","DOIUrl":"https://doi.org/10.1145/3302509.3311051","url":null,"abstract":"In this paper, we propose a technique that attempts to control energy consumption in distributed cyber-physical systems (CPS) in order to improve the level of security of the system. This is in contrast to most existing methods, where the system is set to use a certain level of authentication at design time, such as basic authentication, certificate-based authentication, or no authentication at all. To this end, we propose a notion of authenticatable task graph, which encodes standard task dependencies and allows for authentication tasks to be intermittently inserted into the computation task graph. The optimization objective here is to maximize the number of authentication tasks as well as peer-authentication, while remaining in the system energy bounds. We propose three offline optimization techniques and one online algorithm, where the system can dynamically manage the tradeoff between energy consumption and the level of security in the presence of uncertainties imposed by the physical environment. Our optimization algorithms are validated by a rich set of simulations as well as a real-world case study on a group of unmanned aerial vehicles (UAVs) that are assigned area search tasks and are required to perform peer-authentication within their battery limits.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"563 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127683843","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}
Onur Ayan, Mikhail Vilgelm, M. Klügel, S. Hirche, W. Kellerer
Age-of-Information (AoI) is a recently introduced metric for network operation with sensor applications which quantifies the freshness of data. In the context of networked control systems (NCSs), we compare the worth of the AoI metric with the value-of-information (VoI) metric, which is related to the uncertainty reduction in stochastic processes. First, we show that the uncertainty propagates non-linearly over time depending on system dynamics. Next, we define the value of a new update of the process of interest as a function of AoI and system parameters of the NCSs. We use the aggregated update value as a utility for the centralized scheduling problem in a cellular NCS composed of multiple heterogeneous control loops. By conducting a simulative analysis, we show that prioritizing transmissions with higher VoI improves performance of the NCSs compared with providing fair data freshness to all sub-systems equally.
{"title":"Age-of-information vs. value-of-information scheduling for cellular networked control systems","authors":"Onur Ayan, Mikhail Vilgelm, M. Klügel, S. Hirche, W. Kellerer","doi":"10.1145/3302509.3311050","DOIUrl":"https://doi.org/10.1145/3302509.3311050","url":null,"abstract":"Age-of-Information (AoI) is a recently introduced metric for network operation with sensor applications which quantifies the freshness of data. In the context of networked control systems (NCSs), we compare the worth of the AoI metric with the value-of-information (VoI) metric, which is related to the uncertainty reduction in stochastic processes. First, we show that the uncertainty propagates non-linearly over time depending on system dynamics. Next, we define the value of a new update of the process of interest as a function of AoI and system parameters of the NCSs. We use the aggregated update value as a utility for the centralized scheduling problem in a cellular NCS composed of multiple heterogeneous control loops. By conducting a simulative analysis, we show that prioritizing transmissions with higher VoI improves performance of the NCSs compared with providing fair data freshness to all sub-systems equally.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115951959","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}
Ayan Mukhopadhyay, Geoffrey Pettet, Chinmaya Samal, A. Dubey, Yevgeniy Vorobeychik
The problem of dispatching emergency responders to service traffic accidents, fire, distress calls and crimes plagues urban areas across the globe. While such problems have been extensively looked at, most approaches are offline. Such methodologies fail to capture the dynamically changing environments under which critical emergency response occurs, and therefore, fail to be implemented in practice. Any holistic approach towards creating a pipeline for effective emergency response must also look at other challenges that it subsumes - predicting when and where incidents happen and understanding the changing environmental dynamics. We describe a system that collectively deals with all these problems in an online manner, meaning that the models get updated with streaming data sources. We highlight why such an approach is crucial to the effectiveness of emergency response, and present an algorithmic framework that can compute promising actions for a given decision-theoretic model for responder dispatch. We argue that carefully crafted heuristic measures can balance the trade-off between computational time and the quality of solutions achieved and highlight why such an approach is more scalable and tractable than traditional approaches. We also present an online mechanism for incident prediction, as well as an approach based on recurrent neural networks for learning and predicting environmental features that affect responder dispatch. We compare our methodology with prior state-of-the-art and existing dispatch strategies in the field, which show that our approach results in a reduction in response time of responders with a drastic reduction in computational time.
{"title":"An online decision-theoretic pipeline for responder dispatch","authors":"Ayan Mukhopadhyay, Geoffrey Pettet, Chinmaya Samal, A. Dubey, Yevgeniy Vorobeychik","doi":"10.1145/3302509.3311055","DOIUrl":"https://doi.org/10.1145/3302509.3311055","url":null,"abstract":"The problem of dispatching emergency responders to service traffic accidents, fire, distress calls and crimes plagues urban areas across the globe. While such problems have been extensively looked at, most approaches are offline. Such methodologies fail to capture the dynamically changing environments under which critical emergency response occurs, and therefore, fail to be implemented in practice. Any holistic approach towards creating a pipeline for effective emergency response must also look at other challenges that it subsumes - predicting when and where incidents happen and understanding the changing environmental dynamics. We describe a system that collectively deals with all these problems in an online manner, meaning that the models get updated with streaming data sources. We highlight why such an approach is crucial to the effectiveness of emergency response, and present an algorithmic framework that can compute promising actions for a given decision-theoretic model for responder dispatch. We argue that carefully crafted heuristic measures can balance the trade-off between computational time and the quality of solutions achieved and highlight why such an approach is more scalable and tractable than traditional approaches. We also present an online mechanism for incident prediction, as well as an approach based on recurrent neural networks for learning and predicting environmental features that affect responder dispatch. We compare our methodology with prior state-of-the-art and existing dispatch strategies in the field, which show that our approach results in a reduction in response time of responders with a drastic reduction in computational time.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124479203","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}
Song Fang, K. Johansson, M. Skoglund, H. Sandberg, H. Ishii
In this paper, we introduce the method of two-way coding, a concept originating in communication theory characterizing coding schemes for two-way channels, into (networked) feedback control systems under injection attacks. We first show that the presence of two-way coding can distort the perspective of the attacker on the control system. In general, the distorted viewpoint on the attacker side as a consequence of two-way coding will facilitate detecting the attacks, or restricting what the attacker can do, or even correcting the attack effect. In the particular case of zero-dynamics attacks, if the attacks are to be designed according to the original plant, then they will be easily detected; while if the attacks are designed with respect to the equivalent plant as viewed by the attacker, then under the additional assumption that the plant is stabilizable by static output feedback, the attack effect may be corrected in steady state.
{"title":"Two-way coding in control systems under injection attacks: from attack detection to attack correction","authors":"Song Fang, K. Johansson, M. Skoglund, H. Sandberg, H. Ishii","doi":"10.1145/3302509.3311047","DOIUrl":"https://doi.org/10.1145/3302509.3311047","url":null,"abstract":"In this paper, we introduce the method of two-way coding, a concept originating in communication theory characterizing coding schemes for two-way channels, into (networked) feedback control systems under injection attacks. We first show that the presence of two-way coding can distort the perspective of the attacker on the control system. In general, the distorted viewpoint on the attacker side as a consequence of two-way coding will facilitate detecting the attacks, or restricting what the attacker can do, or even correcting the attack effect. In the particular case of zero-dynamics attacks, if the attacks are to be designed according to the original plant, then they will be easily detected; while if the attacks are designed with respect to the equivalent plant as viewed by the attacker, then under the additional assumption that the plant is stabilizable by static output feedback, the attack effect may be corrected in steady state.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116305391","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}
Kathy Jang, Logan E. Beaver, Behdad Chalaki, Ben Remer, Eugene Vinitsky, Andreas A. Malikopoulos, A. Bayen
Using deep reinforcement learning, we successfully train a set of two autonomous vehicles to lead a fleet of vehicles onto a round-about and then transfer this policy from simulation to a scaled city without fine-tuning. We use Flow, a library for deep reinforcement learning in microsimulators, to train two policies, (1) a policy with noise injected into the state and action space and (2) a policy without any injected noise. In simulation, the autonomous vehicles learn an emergent metering behavior for both policies which allows smooth merging. We then directly transfer this policy without any tuning to the University of Delaware's Scaled Smart City (UDSSC), a 1:25 scale testbed for connected and automated vehicles. We characterize the performance of the transferred policy based on how thoroughly the ramp metering behavior is captured in UDSSC. We show that the noise-free policy results in severe slowdowns and only, occasionally, it exhibits acceptable metering behavior. On the other hand, the noise-injected policy consistently performs an acceptable metering behavior, implying that the noise eventually aids with the zero-shot policy transfer. Finally, the transferred, noise-injected policy leads to a 5% reduction of average travel time and a reduction of 22% in maximum travel time in the UDSSC. Videos of the proposed self-learning controllers can be found at https://sites.google.com/view/iccps-policy-transfer.
{"title":"Simulation to scaled city: zero-shot policy transfer for traffic control via autonomous vehicles","authors":"Kathy Jang, Logan E. Beaver, Behdad Chalaki, Ben Remer, Eugene Vinitsky, Andreas A. Malikopoulos, A. Bayen","doi":"10.1145/3302509.3313784","DOIUrl":"https://doi.org/10.1145/3302509.3313784","url":null,"abstract":"Using deep reinforcement learning, we successfully train a set of two autonomous vehicles to lead a fleet of vehicles onto a round-about and then transfer this policy from simulation to a scaled city without fine-tuning. We use Flow, a library for deep reinforcement learning in microsimulators, to train two policies, (1) a policy with noise injected into the state and action space and (2) a policy without any injected noise. In simulation, the autonomous vehicles learn an emergent metering behavior for both policies which allows smooth merging. We then directly transfer this policy without any tuning to the University of Delaware's Scaled Smart City (UDSSC), a 1:25 scale testbed for connected and automated vehicles. We characterize the performance of the transferred policy based on how thoroughly the ramp metering behavior is captured in UDSSC. We show that the noise-free policy results in severe slowdowns and only, occasionally, it exhibits acceptable metering behavior. On the other hand, the noise-injected policy consistently performs an acceptable metering behavior, implying that the noise eventually aids with the zero-shot policy transfer. Finally, the transferred, noise-injected policy leads to a 5% reduction of average travel time and a reduction of 22% in maximum travel time in the UDSSC. Videos of the proposed self-learning controllers can be found at https://sites.google.com/view/iccps-policy-transfer.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132105940","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}
S. Gautham, Georgios Bakirtzis, Matthew T. Leccadito, R. Klenke, C. Elks
Cyber-physical systems (CPS) are composed of various embedded subsystems (often realized on system on chip technology) and require specialized software, firmware and hardware to coordinate with the rest of the system. These multiple levels of integration expose attack surfaces which can be susceptible to attack vectors that require novel architectural methods to effectively secure against. We present a multilevel monitor architecture cybersecurity approach applied to a flight control system (FCS). We develop formal framework for the architecture using Event Calculus to define the interactions among the monitors and the system under observation.
{"title":"A multilevel cybersecurity and safety monitor for embedded cyber-physical systems: WIP abstract","authors":"S. Gautham, Georgios Bakirtzis, Matthew T. Leccadito, R. Klenke, C. Elks","doi":"10.1145/3302509.3313321","DOIUrl":"https://doi.org/10.1145/3302509.3313321","url":null,"abstract":"Cyber-physical systems (CPS) are composed of various embedded subsystems (often realized on system on chip technology) and require specialized software, firmware and hardware to coordinate with the rest of the system. These multiple levels of integration expose attack surfaces which can be susceptible to attack vectors that require novel architectural methods to effectively secure against. We present a multilevel monitor architecture cybersecurity approach applied to a flight control system (FCS). We develop formal framework for the architecture using Event Calculus to define the interactions among the monitors and the system under observation.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129209909","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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