As Cyber-Physical Systems (CPSs) become more autonomous, it becomes harder for humans who interact with the CPSs to understand the behavior of the systems. Particularly for CPSs that must perform tasks while optimizing for multiple quality objectives and acting under uncertainty, it can be difficult for humans to understand the system behavior generated by an automated planner. This work-in-progress presents an approach at clarifying system behavior through interactive explanation by allowing end-users to ask Why and Why-Not questions about specific behaviors of the system, and providing answers in the form of contrastive explanation.
{"title":"Interactive explanation for planning-based systems: WIP abstract","authors":"Ellin Zhao, Roykrong Sukkerd","doi":"10.1145/3302509.3313322","DOIUrl":"https://doi.org/10.1145/3302509.3313322","url":null,"abstract":"As Cyber-Physical Systems (CPSs) become more autonomous, it becomes harder for humans who interact with the CPSs to understand the behavior of the systems. Particularly for CPSs that must perform tasks while optimizing for multiple quality objectives and acting under uncertainty, it can be difficult for humans to understand the system behavior generated by an automated planner. This work-in-progress presents an approach at clarifying system behavior through interactive explanation by allowing end-users to ask Why and Why-Not questions about specific behaviors of the system, and providing answers in the form of contrastive explanation.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"46 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":"129262203","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}
Machine learning (ML) techniques are increasingly applied to decision-making and control problems in Cyber-Physical Systems among which many are safety-critical, e.g., chemical plants, robotics, autonomous vehicles. Despite the significant benefits brought by ML techniques, they also raise additional safety issues because 1) most expressive and powerful ML models are not transparent and behave as a black box and 2) the training data which plays a crucial role in ML safety is usually incomplete. An important technique to achieve safety for ML models is "Safe Fail", i.e., a model selects a reject option and applies the backup solution, a traditional controller or a human operator for example, when it has low confidence in a prediction. Data-driven models produced by ML algorithms learn from training data, and hence they are only as good as the examples they have learnt. As pointed in [17], ML models work well in the "training space" (i.e., feature space with sufficient training data), but they could not extrapolate beyond the training space. As observed in many previous studies, a feature space that lacks training data generally has a much higher error rate than the one that contains sufficient training samples [31]. Therefore, it is essential to identify the training space and avoid extrapolating beyond the training space. In this paper, we propose an efficient Feature Space Partitioning Tree (FSPT) to address this problem. Using experiments, we also show that, a strong relationship exists between model performance and FSPT score.
{"title":"Towards safe machine learning for CPS: infer uncertainty from training data","authors":"Xiaozhe Gu, A. Easwaran","doi":"10.1145/3302509.3311038","DOIUrl":"https://doi.org/10.1145/3302509.3311038","url":null,"abstract":"Machine learning (ML) techniques are increasingly applied to decision-making and control problems in Cyber-Physical Systems among which many are safety-critical, e.g., chemical plants, robotics, autonomous vehicles. Despite the significant benefits brought by ML techniques, they also raise additional safety issues because 1) most expressive and powerful ML models are not transparent and behave as a black box and 2) the training data which plays a crucial role in ML safety is usually incomplete. An important technique to achieve safety for ML models is \"Safe Fail\", i.e., a model selects a reject option and applies the backup solution, a traditional controller or a human operator for example, when it has low confidence in a prediction. Data-driven models produced by ML algorithms learn from training data, and hence they are only as good as the examples they have learnt. As pointed in [17], ML models work well in the \"training space\" (i.e., feature space with sufficient training data), but they could not extrapolate beyond the training space. As observed in many previous studies, a feature space that lacks training data generally has a much higher error rate than the one that contains sufficient training samples [31]. Therefore, it is essential to identify the training space and avoid extrapolating beyond the training space. In this paper, we propose an efficient Feature Space Partitioning Tree (FSPT) to address this problem. Using experiments, we also show that, a strong relationship exists between model performance and FSPT score.","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":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129240416","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}
Sirat Samyoun, M. A. S. Mondol, I. Emi, J. Stankovic
Adherence to prescribed medical treatments is crucial for health outcomes in chronic diseases. Recent advancements in smartwatch technologies have opened opportunities to use these wearables in improving adherence through reminders and tracking. This paper presents iAdhere, an Apple Watch based system for reminders and tracking adherence to the prescribed activities for stroke patients.
{"title":"iAdhere: A voice interactive assistant to improve adherence to medical treatments: demo abstract","authors":"Sirat Samyoun, M. A. S. Mondol, I. Emi, J. Stankovic","doi":"10.1145/3302509.3313328","DOIUrl":"https://doi.org/10.1145/3302509.3313328","url":null,"abstract":"Adherence to prescribed medical treatments is crucial for health outcomes in chronic diseases. Recent advancements in smartwatch technologies have opened opportunities to use these wearables in improving adherence through reminders and tracking. This paper presents iAdhere, an Apple Watch based system for reminders and tracking adherence to the prescribed activities for stroke patients.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"12 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":"117327897","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}
Programmable Logic Controllers (PLCs) provide a prominent choice of implementation platform for safety-critical industrial control systems. Formal verification provides ways of establishing correctness guarantees, which can be quite important for such safety-critical applications. But since PLC code does not include an analytic model of the system plant, their verification is limited to discrete properties. In this paper, we, thus, start the other way around with hybrid programs that include continuous plant models in addition to discrete control algorithms. Correctness properties of hybrid programs can be formally verified in the theorem prover KeYmaera X that implements differential dynamic logic, dL, for hybrid programs. After verifying the hybrid program, we now present an approach for translating hybrid programs into PLC code. The new HyPLC tool implements this translation of discrete control code of verified hybrid program models to PLC controller code and, vice versa, the translation of existing PLC code into the discrete control actions for a hybrid program given an additional input of the continuous dynamics of the system to be verified. This approach allows for the generation of real controller code while preserving, by compilation, the correctness of a valid and verified hybrid program. PLCs are common cyber-physical interfaces for safety-critical industrial control applications, and HyPLC serves as a pragmatic tool for bridging formal verification of complex cyber-physical systems at the algorithmic level of hybrid programs with the execution layer of concrete PLC implementations.
{"title":"HyPLC","authors":"L. García, Stefan Mitsch, André Platzer","doi":"10.1145/3302509.3311036","DOIUrl":"https://doi.org/10.1145/3302509.3311036","url":null,"abstract":"Programmable Logic Controllers (PLCs) provide a prominent choice of implementation platform for safety-critical industrial control systems. Formal verification provides ways of establishing correctness guarantees, which can be quite important for such safety-critical applications. But since PLC code does not include an analytic model of the system plant, their verification is limited to discrete properties. In this paper, we, thus, start the other way around with hybrid programs that include continuous plant models in addition to discrete control algorithms. Correctness properties of hybrid programs can be formally verified in the theorem prover KeYmaera X that implements differential dynamic logic, dL, for hybrid programs. After verifying the hybrid program, we now present an approach for translating hybrid programs into PLC code. The new HyPLC tool implements this translation of discrete control code of verified hybrid program models to PLC controller code and, vice versa, the translation of existing PLC code into the discrete control actions for a hybrid program given an additional input of the continuous dynamics of the system to be verified. This approach allows for the generation of real controller code while preserving, by compilation, the correctness of a valid and verified hybrid program. PLCs are common cyber-physical interfaces for safety-critical industrial control applications, and HyPLC serves as a pragmatic tool for bridging formal verification of complex cyber-physical systems at the algorithmic level of hybrid programs with the execution layer of concrete PLC implementations.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"52 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":"132281562","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}
This study presents a hardware architecture design to solve the Satisfiability (SAT) problem which can represent various types of control applications in Cyber-Physical Systems (CPS). The proposed architecture adapts an emerging bio-inspired SAT solver, "AmoebaSAT" which possesses the high potentials of parallel computing and is thus suitable for hardware implementation. By exploring several hardware optimization techniques through an advanced high-level design technology (i.e., high-level synthesis), we realized an FPGA-based AmoebaSAT solver applicable to any CPS application whose control rules can be expressed as a SAT instance.
{"title":"FPGA-Based amoeba-inspired SAT solver for cyber-physical systems","authors":"Anh Hoang Ngoc Nguyen, M. Aono, Yuko Hara-Azumi","doi":"10.1145/3302509.3313319","DOIUrl":"https://doi.org/10.1145/3302509.3313319","url":null,"abstract":"This study presents a hardware architecture design to solve the Satisfiability (SAT) problem which can represent various types of control applications in Cyber-Physical Systems (CPS). The proposed architecture adapts an emerging bio-inspired SAT solver, \"AmoebaSAT\" which possesses the high potentials of parallel computing and is thus suitable for hardware implementation. By exploring several hardware optimization techniques through an advanced high-level design technology (i.e., high-level synthesis), we realized an FPGA-based AmoebaSAT solver applicable to any CPS application whose control rules can be expressed as a SAT instance.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"7 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":"114777629","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}
This paper proposes a MATLAB/Simulink benchmark suite for an open-source self-driving system based on Robot Operating System (ROS). In recent years, self-driving systems have been developed around the world. One approach to the development of self-driving systems is the utilization of ROS which is an open-source middleware framework used in the development of robot applications. On the other hand, the popular approach in the automotive industry is the utilization of MATLAB/Simulink which is software for modeling, simulating, and analyzing. MATLAB/Simulink provides an interface between ROS and MATLAB/Simulink that enables to create functionalities of ROS-based robots in MATLAB/Simulink. However, it is not been fully utilized in the development of self-driving systems yet because there are not enough samples for self-driving, and it is difficult for developers to adopt co-development. Therefore, we provide a MATLAB/Simulink benchmark suite for a ROS-based self-driving system called Autoware. Autoware is popular open-source software that provides a complete set of self-driving modules. The provided benchmark contains MATLAB/Simulink samples available in Autoware. They help to design ROS-based self-driving systems using MATLAB/Simulink.
{"title":"MATLAB/Simulink benchmark suite for ROS-based self-driving system: demo abstract","authors":"Shota Tokunaga, Noriyuki Ota, Yoshiharu Tange, Keita Miura, Takuya Azumi","doi":"10.1145/3302509.3313315","DOIUrl":"https://doi.org/10.1145/3302509.3313315","url":null,"abstract":"This paper proposes a MATLAB/Simulink benchmark suite for an open-source self-driving system based on Robot Operating System (ROS). In recent years, self-driving systems have been developed around the world. One approach to the development of self-driving systems is the utilization of ROS which is an open-source middleware framework used in the development of robot applications. On the other hand, the popular approach in the automotive industry is the utilization of MATLAB/Simulink which is software for modeling, simulating, and analyzing. MATLAB/Simulink provides an interface between ROS and MATLAB/Simulink that enables to create functionalities of ROS-based robots in MATLAB/Simulink. However, it is not been fully utilized in the development of self-driving systems yet because there are not enough samples for self-driving, and it is difficult for developers to adopt co-development. Therefore, we provide a MATLAB/Simulink benchmark suite for a ROS-based self-driving system called Autoware. Autoware is popular open-source software that provides a complete set of self-driving modules. The provided benchmark contains MATLAB/Simulink samples available in Autoware. They help to design ROS-based self-driving systems using MATLAB/Simulink.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"25 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":"131019017","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}
This paper presents a data-based model for metro scheduling that aims to minimizes passenger wait time under constraints. In contrast to existing approaches that rely on a statistical model of passenger arrival, we develop a model based on real-world automated fare collection (AFC) data in a metro line of a Korean city for an extended period of time. The model consists of decomposing the travel time for each passenger into wait, ride, and walk times, clustering of passengers by trains they ride and also calculating the number of passengers in each train for any given time. Based on this, for a given train schedule, the total wait time of all the passengers for the entire AFC data period can be calculated. Finally, the minimization problem is formulated using the model under realistic constraints. Refining and validating each component of the model are currently underway before we solve the minimization problem.
{"title":"Data-based model of metro scheduling for passenger wait-time optimization with constraints: WIP abstract","authors":"Minji Kim, Hee-Jung Yoon, S. Son, Y. Eun","doi":"10.1145/3302509.3313324","DOIUrl":"https://doi.org/10.1145/3302509.3313324","url":null,"abstract":"This paper presents a data-based model for metro scheduling that aims to minimizes passenger wait time under constraints. In contrast to existing approaches that rely on a statistical model of passenger arrival, we develop a model based on real-world automated fare collection (AFC) data in a metro line of a Korean city for an extended period of time. The model consists of decomposing the travel time for each passenger into wait, ride, and walk times, clustering of passengers by trains they ride and also calculating the number of passengers in each train for any given time. Based on this, for a given train schedule, the total wait time of all the passengers for the entire AFC data period can be calculated. Finally, the minimization problem is formulated using the model under realistic constraints. Refining and validating each component of the model are currently underway before we solve the minimization problem.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"58 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":"127978594","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}
Xin Lou, Cuong Tran, Rui Tan, David K. Y. Yau, Z. Kalbarczyk
Recent attacks against cyber-physical systems (CPSes) show that traditional reliance on isolation for security is insufficient. This paper develops efficient assessment and mitigation of an attack's impact as a system's built-in mechanisms. We focus on a general class of attacks, which we call time delay attack, that delays the transmissions of control data packets in a linear CPS control system. Our attack impact assessment, which is based on a joint stability-safety criterion, consists of (i) a machine learning (ML) based safety classification, and (ii) a tandem stability-safety classification that exploits a basic relationship between stability and safety, namely that an unstable system must be unsafe whereas a stable system may not be safe. The ML addresses a state explosion problem in the safety classification, whereas the tandem structure reduces false negatives in detecting unsafety arising from imperfect ML. We apply our approach to assess the impact of the attack on power grid automatic generation control, and accordingly develop a two-tiered mitigation that tunes the control gain automatically to restore safety where necessary and shed load only if the tuning is insufficient. Extensive simulations based on a 37-bus system model are conducted to evaluate the effectiveness of our assessment and mitigation approaches.
{"title":"Assessing and mitigating impact of time delay attack: a case study for power grid frequency control","authors":"Xin Lou, Cuong Tran, Rui Tan, David K. Y. Yau, Z. Kalbarczyk","doi":"10.1145/3302509.3311042","DOIUrl":"https://doi.org/10.1145/3302509.3311042","url":null,"abstract":"Recent attacks against cyber-physical systems (CPSes) show that traditional reliance on isolation for security is insufficient. This paper develops efficient assessment and mitigation of an attack's impact as a system's built-in mechanisms. We focus on a general class of attacks, which we call time delay attack, that delays the transmissions of control data packets in a linear CPS control system. Our attack impact assessment, which is based on a joint stability-safety criterion, consists of (i) a machine learning (ML) based safety classification, and (ii) a tandem stability-safety classification that exploits a basic relationship between stability and safety, namely that an unstable system must be unsafe whereas a stable system may not be safe. The ML addresses a state explosion problem in the safety classification, whereas the tandem structure reduces false negatives in detecting unsafety arising from imperfect ML. We apply our approach to assess the impact of the attack on power grid automatic generation control, and accordingly develop a two-tiered mitigation that tunes the control gain automatically to restore safety where necessary and shed load only if the tuning is insufficient. Extensive simulations based on a 37-bus system model are conducted to evaluate the effectiveness of our assessment and mitigation approaches.","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":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114184251","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}
Gregor B. Banusic, Rupak Majumdar, M. Pirron, Anne-Kathrin Schmuck, D. Zufferey
Robotics applications are typically programmed in low-level imperative programming languages, leaving the programmer to deal with dynamic controllers affecting the physical state, geometric constraints on components, and concurrency and synchronization. The combination of these features -dynamics, geometry, and concurrency- makes developing robotic applications difficult. We present PGCD, a programming model for robotics applications consisting of assemblies of robotic components, together with its runtime and a verifier. PGCD combines message-passing concurrent processes with motion primitives, which represent continuous evolution of trajectories in geometric space under the action of dynamic controllers, and explicit modeling of geometric frame shifts, which allow relative coordinate transformations between components evolving in space. We describe a verification algorithm for PGCD programs based on model checking and SMT solvers that statically verifies concurrency-related properties such as absence of deadlocks and geometric invariants such as absence of collision during motion. We have implemented a runtime for PGCD programs that compiles down to imperative code on top of ROS and runs directly on robotic hardware. We illustrate the programming model and reasoning principles by building a number of statically verified robotic manipulation programs on top of 3D-printed robotic arm and cart assemblies.
{"title":"PGCD","authors":"Gregor B. Banusic, Rupak Majumdar, M. Pirron, Anne-Kathrin Schmuck, D. Zufferey","doi":"10.1145/3302509.3311052","DOIUrl":"https://doi.org/10.1145/3302509.3311052","url":null,"abstract":"Robotics applications are typically programmed in low-level imperative programming languages, leaving the programmer to deal with dynamic controllers affecting the physical state, geometric constraints on components, and concurrency and synchronization. The combination of these features -dynamics, geometry, and concurrency- makes developing robotic applications difficult. We present PGCD, a programming model for robotics applications consisting of assemblies of robotic components, together with its runtime and a verifier. PGCD combines message-passing concurrent processes with motion primitives, which represent continuous evolution of trajectories in geometric space under the action of dynamic controllers, and explicit modeling of geometric frame shifts, which allow relative coordinate transformations between components evolving in space. We describe a verification algorithm for PGCD programs based on model checking and SMT solvers that statically verifies concurrency-related properties such as absence of deadlocks and geometric invariants such as absence of collision during motion. We have implemented a runtime for PGCD programs that compiles down to imperative code on top of ROS and runs directly on robotic hardware. We illustrate the programming model and reasoning principles by building a number of statically verified robotic manipulation programs on top of 3D-printed robotic arm and cart assemblies.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"35 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":"116723658","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}
Opacity is an important information-flow security property in the analysis of cyber-physical systems. In this abstract, we extend the concept of opacity to systems whose output sets are equipped with metrics. A new concept called approximate opacity is proposed in order to quantitatively evaluate the security guarantee level with respect to the measurement precision of the intruder. Then we propose a new simulation-type relation called approximate opacity preserving simulation relations, which characterizes how close two systems are in terms of the satisfaction of approximate opacity. We also discuss how to construct approximate opacity preserving symbolic models for a class of discrete-time control systems.
{"title":"Towards approximate opacity of cyber-physical system: WIP abstract","authors":"Xiang Yin, Majid Zamani","doi":"10.1145/3302509.3313316","DOIUrl":"https://doi.org/10.1145/3302509.3313316","url":null,"abstract":"Opacity is an important information-flow security property in the analysis of cyber-physical systems. In this abstract, we extend the concept of opacity to systems whose output sets are equipped with metrics. A new concept called approximate opacity is proposed in order to quantitatively evaluate the security guarantee level with respect to the measurement precision of the intruder. Then we propose a new simulation-type relation called approximate opacity preserving simulation relations, which characterizes how close two systems are in terms of the satisfaction of approximate opacity. We also discuss how to construct approximate opacity preserving symbolic models for a class of discrete-time control systems.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"66 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":"125209846","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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