Data-driven modeling usually suffers from data sparsity, especially for large-scale modeling for urban phenomena based on single-source urban infrastructure data under fine-grained spatial-temporal contexts. To address this challenge, we motivate, design and implement UrbanCPS, a cyber-physical system with heterogeneous model integration, based on extremely-large multi-source infrastructures in a Chinese city Shenzhen, involving 42 thousand vehicles, 10 million residents, and 16 million smartcards. Based on temporal, spatial and contextual contexts, we formulate an optimization problem about how to optimally integrate models based on highly-diverse datasets, under three practical issues, i.e., heterogeneity of models, input data sparsity or unknown ground truth. We further propose a real-world application called Speedometer, inferring real-time traffic speeds in urban areas. The evaluation results show that compared to a state-of-the-art system, Speedometer increases the inference accuracy by 21% on average.
{"title":"UrbanCPS: a cyber-physical system based on multi-source big infrastructure data for heterogeneous model integration","authors":"Desheng Zhang, Juanjuan Zhao, Fan Zhang, T. He","doi":"10.1145/2735960.2735985","DOIUrl":"https://doi.org/10.1145/2735960.2735985","url":null,"abstract":"Data-driven modeling usually suffers from data sparsity, especially for large-scale modeling for urban phenomena based on single-source urban infrastructure data under fine-grained spatial-temporal contexts. To address this challenge, we motivate, design and implement UrbanCPS, a cyber-physical system with heterogeneous model integration, based on extremely-large multi-source infrastructures in a Chinese city Shenzhen, involving 42 thousand vehicles, 10 million residents, and 16 million smartcards. Based on temporal, spatial and contextual contexts, we formulate an optimization problem about how to optimally integrate models based on highly-diverse datasets, under three practical issues, i.e., heterogeneity of models, input data sparsity or unknown ground truth. We further propose a real-world application called Speedometer, inferring real-time traffic speeds in urban areas. The evaluation results show that compared to a state-of-the-art system, Speedometer increases the inference accuracy by 21% on average.","PeriodicalId":344612,"journal":{"name":"Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121063724","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}
Peng Deng, Fabio Cremona, Qi Zhu, M. Natale, Haibo Zeng
Synchronous reactive models are used by automotive suppliers to develop functionality delivered as AUTOSAR components to system integrators (OEMs). Integrators must then generate a task implementation from runnables in AUTOSAR components and deploy tasks onto CPU cores, while preserving timing and resource constraints. In this work, we propose an integrated synthesis flow that addresses both sides of the supply chain. On the supplier side, from synchronous models, we generate AUTOSAR runnables that promote reuse and ease the job of finding schedulable implementations. On the integrator side, we find the mapping of runnables onto tasks and allocation of tasks on cores that satisfy the timing constraints and are memory efficient.
{"title":"A model-based synthesis flow for automotive CPS","authors":"Peng Deng, Fabio Cremona, Qi Zhu, M. Natale, Haibo Zeng","doi":"10.1145/2735960.2735972","DOIUrl":"https://doi.org/10.1145/2735960.2735972","url":null,"abstract":"Synchronous reactive models are used by automotive suppliers to develop functionality delivered as AUTOSAR components to system integrators (OEMs). Integrators must then generate a task implementation from runnables in AUTOSAR components and deploy tasks onto CPU cores, while preserving timing and resource constraints. In this work, we propose an integrated synthesis flow that addresses both sides of the supply chain. On the supplier side, from synchronous models, we generate AUTOSAR runnables that promote reuse and ease the job of finding schedulable implementations. On the integrator side, we find the mapping of runnables onto tasks and allocation of tasks on cores that satisfy the timing constraints and are memory efficient.","PeriodicalId":344612,"journal":{"name":"Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129759452","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}
Cooperative collision avoidance systems rely on communication between vehicles to achieve the objective of automated or human-dependent crash avoidance. In this paper we investigate the mutual coupling of communication component and the safety application in cooperative collision warning systems. These systems are warning based collision avoidance systems that are currently under field test. We present a comprehensive co-simulation modeling framework which allows modeling and study of the entire system including vehicle dynamics, communication protocols, and collision detection/warning algorithms. Using this model, we show that in designs where the safety application and communication components are designed separately and agnostic to each other, system performance requires significantly higher network resources. Alternate content- and network-aware design strategies are shown to significantly reduce the required resources, resulting in significant reliability improvements. However, the cost of such strategies is mutual coupling of the performance of safety application and communication components. We show that such coupling can be effectively controlled in desired operation ranges for each component, leading to robust systems. The presented framework introduces a method for the study of a wide spectrum of communication dependent vehicular cyber-physical systems.
{"title":"Analysis of the coupling of communication network and safety application in cooperative collision warning systems","authors":"Y. P. Fallah, Masoumeh Kalantari Khandani","doi":"10.1145/2735960.2735975","DOIUrl":"https://doi.org/10.1145/2735960.2735975","url":null,"abstract":"Cooperative collision avoidance systems rely on communication between vehicles to achieve the objective of automated or human-dependent crash avoidance. In this paper we investigate the mutual coupling of communication component and the safety application in cooperative collision warning systems. These systems are warning based collision avoidance systems that are currently under field test. We present a comprehensive co-simulation modeling framework which allows modeling and study of the entire system including vehicle dynamics, communication protocols, and collision detection/warning algorithms. Using this model, we show that in designs where the safety application and communication components are designed separately and agnostic to each other, system performance requires significantly higher network resources. Alternate content- and network-aware design strategies are shown to significantly reduce the required resources, resulting in significant reliability improvements. However, the cost of such strategies is mutual coupling of the performance of safety application and communication components. We show that such coupling can be effectively controlled in desired operation ranges for each component, leading to robust systems. The presented framework introduces a method for the study of a wide spectrum of communication dependent vehicular cyber-physical systems.","PeriodicalId":344612,"journal":{"name":"Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129307209","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}
Zhijian He, Shuai Li, Zhaoyan Shen, Muhammad Umer Khan, Z. Shao, Qixin Wang
Cyber-physical system (CPS) features the interaction between embedded systems and the physical world. In this paper, we focus on a CPS using unmanned quadcopters to interact with the environment to monitor smog propagation. Our quadcopters shall be equipped with various sensors including smog sensor, wind speed sensor, and GPS; and shall be able to fly omni-directionally in open air space. Compared to ground sensing, our approach shall enable 3D monitoring of smog propagation. Compared to conventional balloon based aerial sensing, the vast number of cheap quadcopters and high mobile speed shall enable better monitoring granularity and adaptability. In our preliminary study [1], we start with modeling and optimizing the control of a single quadcopter, taking into consideration partial differential equations governing the smog propagation, and nonlinear dynamic model of the quadcopter. The optimized single quadcopter control strategy is then extended for multiple quadcopters, under an additional formation control constraint. The strategy is validated with simulation. Effort is now underway to implement the preliminary study strategy in Arduino based quadcopters. Through this study, we aim not only to realize a novel CPS application, but also to build a experiment test-bed, to explore insights on how to exploit prior-knowledge to optimize interactions between embedded robotic systems and physical world in CPS.
{"title":"A quadcopter swarm for active monitoring of smog propagation","authors":"Zhijian He, Shuai Li, Zhaoyan Shen, Muhammad Umer Khan, Z. Shao, Qixin Wang","doi":"10.1145/2735960.2735988","DOIUrl":"https://doi.org/10.1145/2735960.2735988","url":null,"abstract":"Cyber-physical system (CPS) features the interaction between embedded systems and the physical world. In this paper, we focus on a CPS using unmanned quadcopters to interact with the environment to monitor smog propagation. Our quadcopters shall be equipped with various sensors including smog sensor, wind speed sensor, and GPS; and shall be able to fly omni-directionally in open air space. Compared to ground sensing, our approach shall enable 3D monitoring of smog propagation. Compared to conventional balloon based aerial sensing, the vast number of cheap quadcopters and high mobile speed shall enable better monitoring granularity and adaptability. In our preliminary study [1], we start with modeling and optimizing the control of a single quadcopter, taking into consideration partial differential equations governing the smog propagation, and nonlinear dynamic model of the quadcopter. The optimized single quadcopter control strategy is then extended for multiple quadcopters, under an additional formation control constraint. The strategy is validated with simulation. Effort is now underway to implement the preliminary study strategy in Arduino based quadcopters. Through this study, we aim not only to realize a novel CPS application, but also to build a experiment test-bed, to explore insights on how to exploit prior-knowledge to optimize interactions between embedded robotic systems and physical world in CPS.","PeriodicalId":344612,"journal":{"name":"Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131902115","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}
Zhichuan Huang, David Corrigan, Ting Zhu, Hongyao Luo, X. Zhan, Y. Gu
Due to limited energy storage units in microgrids, how to regulate peak demand is one of the main challenges. Thus, researchers propose different techniques to flatten peak demand in individual residential buildings. However, if each home in the grid flattens peak demand only with its own power consumption information, it is possible that peak demand of the microgrid would not be flattened but only shifted to another period. Therefore, it is critical for homes to cooperate with each other to flatten peak demand. In this paper, we utilize the power-voltage relationship in individual homes to enable that each home can infer the information of power consumption in the community by locally monitoring the voltage value on the common power line. The inferred information is then used for homes to flatten peak demand of the microgrids in a distributed manner. Furthermore, we leverage existing thermal appliances (e.g., water heaters) as thermal "batteries" in individual homes instead of purchasing batteries to flatten peak demand. We evaluate our system's performance by conducting experiments and extensive empirical data driven simulations. Evaluation results indicate that our design enables homes to effectively flatten peak demand by more than 29% without affecting homeowners' behaviors.
{"title":"Exploring power-voltage relationship for distributed peak demand flattening in microgrids","authors":"Zhichuan Huang, David Corrigan, Ting Zhu, Hongyao Luo, X. Zhan, Y. Gu","doi":"10.1145/2735960.2735968","DOIUrl":"https://doi.org/10.1145/2735960.2735968","url":null,"abstract":"Due to limited energy storage units in microgrids, how to regulate peak demand is one of the main challenges. Thus, researchers propose different techniques to flatten peak demand in individual residential buildings. However, if each home in the grid flattens peak demand only with its own power consumption information, it is possible that peak demand of the microgrid would not be flattened but only shifted to another period. Therefore, it is critical for homes to cooperate with each other to flatten peak demand. In this paper, we utilize the power-voltage relationship in individual homes to enable that each home can infer the information of power consumption in the community by locally monitoring the voltage value on the common power line. The inferred information is then used for homes to flatten peak demand of the microgrids in a distributed manner. Furthermore, we leverage existing thermal appliances (e.g., water heaters) as thermal \"batteries\" in individual homes instead of purchasing batteries to flatten peak demand. We evaluate our system's performance by conducting experiments and extensive empirical data driven simulations. Evaluation results indicate that our design enables homes to effectively flatten peak demand by more than 29% without affecting homeowners' behaviors.","PeriodicalId":344612,"journal":{"name":"Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126654588","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}
Ming Jin, L. Ratliff, Ioannis C. Konstantakopoulos, C. Spanos, S. Sastry
Through a social game, we integrate building occupants into the control and management of an office building that is instrumented with networked embedded systems for sensing and actuation. The goal of the social game is to both incentivize building occupants to be more energy efficient and learn behavioral models for occupants so that the building can be made sustainable through automation. Given a generative model for the occupants behavior in the competitive environment created by the social game, we develop a method for learning the parameters of the behavioral model as we conduct the experiment by adopting a learning to learn framework. Using tools from statistical learning, we provide bounds on the parameter inference error. In addition, we provide an algorithm for computing the stopping time required for a specified level of confidence in estimation. We show the performance of our algorithm in several examples.
{"title":"REST: a reliable estimation of stopping time algorithm for social game experiments","authors":"Ming Jin, L. Ratliff, Ioannis C. Konstantakopoulos, C. Spanos, S. Sastry","doi":"10.1145/2735960.2735974","DOIUrl":"https://doi.org/10.1145/2735960.2735974","url":null,"abstract":"Through a social game, we integrate building occupants into the control and management of an office building that is instrumented with networked embedded systems for sensing and actuation. The goal of the social game is to both incentivize building occupants to be more energy efficient and learn behavioral models for occupants so that the building can be made sustainable through automation. Given a generative model for the occupants behavior in the competitive environment created by the social game, we develop a method for learning the parameters of the behavioral model as we conduct the experiment by adopting a learning to learn framework. Using tools from statistical learning, we provide bounds on the parameter inference error. In addition, we provide an algorithm for computing the stopping time required for a specified level of confidence in estimation. We show the performance of our algorithm in several examples.","PeriodicalId":344612,"journal":{"name":"Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems","volume":"174 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114093960","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 deals with the problem of designing a distributed fault detection algorithm for nonlinear large-scale systems. In the proposed algorithm, instead of a central detection node, several interconnected local detectors (LD) are employed. Each LD has a limited observation of the system's state and communicates with its neighbors to exchange processed information. The outlet of the detection nodes is the collective probability of failure associated with the system's fault mode. Simulation results illustrate the efficiency of the proposed approach and prove that the stronger communication amongst the LDs will lead to more reliable and faster results.
{"title":"Distributed fault detection of nonlinear large-scale dynamic systems","authors":"E. Noursadeghi, I. Raptis","doi":"10.1145/2735960.2735981","DOIUrl":"https://doi.org/10.1145/2735960.2735981","url":null,"abstract":"This paper deals with the problem of designing a distributed fault detection algorithm for nonlinear large-scale systems. In the proposed algorithm, instead of a central detection node, several interconnected local detectors (LD) are employed. Each LD has a limited observation of the system's state and communicates with its neighbors to exchange processed information. The outlet of the detection nodes is the collective probability of failure associated with the system's fault mode. Simulation results illustrate the efficiency of the proposed approach and prove that the stronger communication amongst the LDs will lead to more reliable and faster results.","PeriodicalId":344612,"journal":{"name":"Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116801184","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}
Embedded systems use increasingly complex software and are evolving into cyber-physical systems (CPS) with sophisticated interaction and coupling between physical and computational processes. Many CPS operate in safety-critical environments and have stringent certification, reliability, and correctness requirements. These systems undergo changes throughout their lifetimes, where either the software or physical hardware is updated in subsequent design iterations. One source of failure in safety-critical CPS is when there are unstated assumptions in either the physical or cyber parts of the system, and new components do not match those assumptions. In this work, we present an automated method towards identifying unstated assumptions in CPS. Dynamic specifications in the form of candidate invariants of both the software and physical components are identified using dynamic analysis (executing and/or simulating the system implementation or model thereof). A prototype tool called Hynger (for HYbrid iNvariant GEneratoR) was developed that instruments Simulink/Stateflow (SLSF) model diagrams to generate traces in the input format compatible with the Daikon invariant inference tool, which has been extensively applied to software systems. Hynger, in conjunction with Daikon, is able to detect candidate invariants of several CPS case studies. We use the running example of a DC-to-DC power converter, and demonstrate that Hynger can detect a specification mismatch where a tolerance assumed by the software is violated due to a plant change.
{"title":"Cyber-physical specification mismatch identification with dynamic analysis","authors":"Taylor T. Johnson, Stanley Bak, S. Drager","doi":"10.1145/2735960.2735979","DOIUrl":"https://doi.org/10.1145/2735960.2735979","url":null,"abstract":"Embedded systems use increasingly complex software and are evolving into cyber-physical systems (CPS) with sophisticated interaction and coupling between physical and computational processes. Many CPS operate in safety-critical environments and have stringent certification, reliability, and correctness requirements. These systems undergo changes throughout their lifetimes, where either the software or physical hardware is updated in subsequent design iterations. One source of failure in safety-critical CPS is when there are unstated assumptions in either the physical or cyber parts of the system, and new components do not match those assumptions. In this work, we present an automated method towards identifying unstated assumptions in CPS. Dynamic specifications in the form of candidate invariants of both the software and physical components are identified using dynamic analysis (executing and/or simulating the system implementation or model thereof). A prototype tool called Hynger (for HYbrid iNvariant GEneratoR) was developed that instruments Simulink/Stateflow (SLSF) model diagrams to generate traces in the input format compatible with the Daikon invariant inference tool, which has been extensively applied to software systems. Hynger, in conjunction with Daikon, is able to detect candidate invariants of several CPS case studies. We use the running example of a DC-to-DC power converter, and demonstrate that Hynger can detect a specification mismatch where a tolerance assumed by the software is violated due to a plant change.","PeriodicalId":344612,"journal":{"name":"Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123532418","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 adaptive varying-rate (AVR) task model has been proposed as a means of modeling certain physically-derived constraints in CPS's in a manner that is more accurate (less pessimistic) than is possible using prior task models from real-time scheduling theory. Existing work on schedulability analysis of systems of AVR tasks is primarily restricted to fixed-priority scheduling; this paper establishes schedulability analysis results for systems of AVR and sporadic tasks under Earliest Deadline First (EDF) scheduling. The proposed analysis techniques are evaluated both theoretically via the speedup factor metric, and experimentally via schedulability experiments on randomly-generated task systems.
{"title":"Uniprocessor EDF scheduling of AVR task systems","authors":"Zhishan Guo, Sanjoy Baruah","doi":"10.1145/2735960.2735976","DOIUrl":"https://doi.org/10.1145/2735960.2735976","url":null,"abstract":"The adaptive varying-rate (AVR) task model has been proposed as a means of modeling certain physically-derived constraints in CPS's in a manner that is more accurate (less pessimistic) than is possible using prior task models from real-time scheduling theory. Existing work on schedulability analysis of systems of AVR tasks is primarily restricted to fixed-priority scheduling; this paper establishes schedulability analysis results for systems of AVR and sporadic tasks under Earliest Deadline First (EDF) scheduling. The proposed analysis techniques are evaluated both theoretically via the speedup factor metric, and experimentally via schedulability experiments on randomly-generated task systems.","PeriodicalId":344612,"journal":{"name":"Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127704617","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}
For better controllability and energy-efficiency, more vehicle functions are being implemented via electronic control systems in place of traditional mechanical control systems. However, such transitions are creating new, unprecedented risks such as software bugs or hardware glitches, all of which can lead to serious safety risks. Recent real-world examples and research literature have been covering them under the name of vehicle misbehavior. In this paper, we present a new way of checking norm operations, called BAD (Brake Anomaly Detection), which detects any vehicle misbehavior in the Brake-by-Wire system. We focus on the braking system since it is a prototypical safety-critical and cyber-physical system. We first propose a new method for constructing norm models of braking and then show how anomalies are detected by BAD using the constructed models. Finally, we discuss how to verify the results, especially in the context of false positives. Our evaluation results show that BAD can effectively detect various types of anomaly in the braking system.
{"title":"CPS approach to checking norm operation of a brake-by-wire system","authors":"Kyong-Tak Cho, K. Shin, Taejoon Park","doi":"10.1145/2735960.2735977","DOIUrl":"https://doi.org/10.1145/2735960.2735977","url":null,"abstract":"For better controllability and energy-efficiency, more vehicle functions are being implemented via electronic control systems in place of traditional mechanical control systems. However, such transitions are creating new, unprecedented risks such as software bugs or hardware glitches, all of which can lead to serious safety risks. Recent real-world examples and research literature have been covering them under the name of vehicle misbehavior. In this paper, we present a new way of checking norm operations, called BAD (Brake Anomaly Detection), which detects any vehicle misbehavior in the Brake-by-Wire system. We focus on the braking system since it is a prototypical safety-critical and cyber-physical system. We first propose a new method for constructing norm models of braking and then show how anomalies are detected by BAD using the constructed models. Finally, we discuss how to verify the results, especially in the context of false positives. Our evaluation results show that BAD can effectively detect various types of anomaly in the braking system.","PeriodicalId":344612,"journal":{"name":"Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133356489","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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