Pub Date : 2020-04-01DOI: 10.1109/iccps48487.2020.00003
{"title":"ICCPS 2020 Breaker Page","authors":"","doi":"10.1109/iccps48487.2020.00003","DOIUrl":"https://doi.org/10.1109/iccps48487.2020.00003","url":null,"abstract":"","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126740463","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}
Pub Date : 2020-04-01DOI: 10.1109/iccps48487.2020.00006
{"title":"ICCPS 2020 Committees","authors":"","doi":"10.1109/iccps48487.2020.00006","DOIUrl":"https://doi.org/10.1109/iccps48487.2020.00006","url":null,"abstract":"","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122332065","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}
Pub Date : 2020-04-01DOI: 10.1109/ICCPS48487.2020.00037
Nathan Allen, P. Roop
Cyber-Physical Systems are being used in "safety-critical" domains and have strict timing constraints, meaning that time predictability of the implementations is highly important. In the event that these timing constraints are violated, the correct operation of the system is no longer guaranteed, and serious consequences may occur. Typically, such systems are implemented in software and executed on processors optimised for average-case performance leading to implementations that are difficult, if not impossible, to analyse for their worst case.We propose an approach which is capable of generating hardware implementations of such systems in a semantics-directed manner, ensuring predictability of the final design. Additionally, we present a schema which is used in the description of such Hybrid Systems, captured as Hybrid Input-Output Automata, which is used in this process. Through the example of a grid of cardiac cells and other industrial examples, we show that this approach generates implementations which are almost 15 times faster than an 800MHz ARM Cortex A-9 in the average case, while maintaining timing predictability and having a Worst Case Reaction Time which is over 3,000 times smaller.
网络物理系统被用于“安全关键”领域，并且有严格的时间限制，这意味着实现的时间可预测性非常重要。一旦违反这些时序约束，系统的正确运行将不再得到保证，并可能产生严重的后果。通常，这样的系统是在软件中实现的，并在针对平均情况性能进行优化的处理器上执行，导致很难(如果不是不可能的话)分析最坏情况的实现。我们提出了一种能够以语义导向的方式生成此类系统的硬件实现的方法，确保最终设计的可预测性。此外，我们提出了一种用于描述这种混合系统的模式，称为混合输入-输出自动机，用于此过程。通过心脏细胞网格的例子和其他工业例子，我们表明，这种方法产生的实现在平均情况下比800MHz ARM Cortex a -9快近15倍，同时保持时间可预测性，并具有超过3000倍的最坏情况反应时间。
{"title":"Semantics-Directed Hardware Generation of Hybrid Systems","authors":"Nathan Allen, P. Roop","doi":"10.1109/ICCPS48487.2020.00037","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00037","url":null,"abstract":"Cyber-Physical Systems are being used in \"safety-critical\" domains and have strict timing constraints, meaning that time predictability of the implementations is highly important. In the event that these timing constraints are violated, the correct operation of the system is no longer guaranteed, and serious consequences may occur. Typically, such systems are implemented in software and executed on processors optimised for average-case performance leading to implementations that are difficult, if not impossible, to analyse for their worst case.We propose an approach which is capable of generating hardware implementations of such systems in a semantics-directed manner, ensuring predictability of the final design. Additionally, we present a schema which is used in the description of such Hybrid Systems, captured as Hybrid Input-Output Automata, which is used in this process. Through the example of a grid of cardiac cells and other industrial examples, we show that this approach generates implementations which are almost 15 times faster than an 800MHz ARM Cortex A-9 in the average case, while maintaining timing predictability and having a Worst Case Reaction Time which is over 3,000 times smaller.","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114091336","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}
Pub Date : 2020-04-01DOI: 10.1109/ICCPS48487.2020.00022
Balaji Balasubramaniam, H. Bagheri, Sebastian G. Elbaum, Justin M. Bradley
Successful cyber-physical system controllers evolve as they are refined, extended, and adapted to new systems and contexts. This evolution occurs in the controller design and also in its software implementation. Model-based design and controller synthesis can help to synchronize this evolution of design and software, but such synchronization is rarely complete as software tends to also evolve in response to elements rarely present in a control model, leading to mismatches between the control design and the software. In this paper we perform a first-of-it-skind study on the evolution of two popular open-source safety-critical autopilot control software – ArduPilot, and Paparazzi, to better understand how controllers evolve and the space of potential mismatches between control design and their software implementation. We then use that understanding to prototype a technique that can generate mutated versions of code to mimic evolution to assess its impact on a controller’s behavior.We find that 1) control software evolves quickly and controllers are rewritten in their entirety over their lifetime, implying that the design, synthesis, and implementation of controllers should also support incremental evolution, 2) many software changes stem from an inherent mismatch between continuous physical models and their corresponding discrete software implementation, but also from the mishandling of exceptional conditions, and limitations and distinct data representation of the underlying computing architecture, 3) small code changes can have a dramatic effect in a controller’s behavior, implying that further support is needed to bridge these mismatches as carefully verified model properties may not necessarily translate to its software implementation.
{"title":"Investigating Controller Evolution and Divergence through Mining and Mutation*","authors":"Balaji Balasubramaniam, H. Bagheri, Sebastian G. Elbaum, Justin M. Bradley","doi":"10.1109/ICCPS48487.2020.00022","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00022","url":null,"abstract":"Successful cyber-physical system controllers evolve as they are refined, extended, and adapted to new systems and contexts. This evolution occurs in the controller design and also in its software implementation. Model-based design and controller synthesis can help to synchronize this evolution of design and software, but such synchronization is rarely complete as software tends to also evolve in response to elements rarely present in a control model, leading to mismatches between the control design and the software. In this paper we perform a first-of-it-skind study on the evolution of two popular open-source safety-critical autopilot control software – ArduPilot, and Paparazzi, to better understand how controllers evolve and the space of potential mismatches between control design and their software implementation. We then use that understanding to prototype a technique that can generate mutated versions of code to mimic evolution to assess its impact on a controller’s behavior.We find that 1) control software evolves quickly and controllers are rewritten in their entirety over their lifetime, implying that the design, synthesis, and implementation of controllers should also support incremental evolution, 2) many software changes stem from an inherent mismatch between continuous physical models and their corresponding discrete software implementation, but also from the mishandling of exceptional conditions, and limitations and distinct data representation of the underlying computing architecture, 3) small code changes can have a dramatic effect in a controller’s behavior, implying that further support is needed to bridge these mismatches as carefully verified model properties may not necessarily translate to its software implementation.","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123203390","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}
Pub Date : 2020-04-01DOI: 10.1109/ICCPS48487.2020.00016
Sara Mohammadinejad, Jyotirmoy V. Deshmukh, Aniruddh Gopinath Puranic
Many complex cyber-physical systems can be modeled as heterogeneous components interacting with each other in real-time. We assume that the correctness of each component can be specified as a requirement satisfied by the output signals produced by the component, and that such an output guarantee is expressed in a real-time temporal logic such as Signal Temporal Logic (STL). In this paper, we hypothesize that a large subset of input signals for which the corresponding output signals satisfy the output requirement can also be compactly described using an STL formula that we call the environment assumption. We propose an algorithm to mine such an environment assumption using a supervised learning technique. Essentially, our algorithm treats the environment assumption as a classifier that labels input signals as good if the corresponding output signal satisfies the output requirement, and as bad otherwise. Our learning method simultaneously learns the structure of the STL formula as well as the values of the numeric constants appearing in the formula.1 To achieve this, we combine a procedure to systematically enumerate candidate Parametric STL (PSTL) formulas, with a decision-tree based approach to learn parameter values. We demonstrate experimental results on real world data from several domains including transportation and health care.
{"title":"Mining Environment Assumptions for Cyber-Physical System Models","authors":"Sara Mohammadinejad, Jyotirmoy V. Deshmukh, Aniruddh Gopinath Puranic","doi":"10.1109/ICCPS48487.2020.00016","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00016","url":null,"abstract":"Many complex cyber-physical systems can be modeled as heterogeneous components interacting with each other in real-time. We assume that the correctness of each component can be specified as a requirement satisfied by the output signals produced by the component, and that such an output guarantee is expressed in a real-time temporal logic such as Signal Temporal Logic (STL). In this paper, we hypothesize that a large subset of input signals for which the corresponding output signals satisfy the output requirement can also be compactly described using an STL formula that we call the environment assumption. We propose an algorithm to mine such an environment assumption using a supervised learning technique. Essentially, our algorithm treats the environment assumption as a classifier that labels input signals as good if the corresponding output signal satisfies the output requirement, and as bad otherwise. Our learning method simultaneously learns the structure of the STL formula as well as the values of the numeric constants appearing in the formula.1 To achieve this, we combine a procedure to systematically enumerate candidate Parametric STL (PSTL) formulas, with a decision-tree based approach to learn parameter values. We demonstrate experimental results on real world data from several domains including transportation and health care.","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116688137","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}
Pub Date : 2020-04-01DOI: 10.1109/ICCPS48487.2020.00014
Abdullah Al Zishan, Moosa Moghimi Haji, Omid Ardakanian
We present a reputation-based framework for allocating power to plug-in electric vehicles (EVs) in the smart grid. In this framework, the available capacity of the distribution network measured by distribution-level phasor measurement units is divided in a proportionally fair manner among connected EVs, considering their demands and self-declared deadlines. To encourage users to estimate their deadlines more precisely and conservatively, a weight is assigned to a each deadline based on the user’s reputation, which comprises two kinds of evidence: deadlines declared before and after the actual departure times in the recent past. Assuming reliable communication between sensors installed in the network and charging stations, we design a decentralized algorithm which allows the users to independently compute their fair share based on signals received from upstream sensors without sharing their private information, e.g., their deadline, with a central scheduler. We prove that this algorithm achieves quadratic convergence under specific conditions and evaluate it empirically on a test distribution network by comparing it with a centralized algorithm which solves the same optimization problem, a decentralized gradient-projection algorithm with linear convergence, and earliest-deadline-first and least-laxity-first scheduling policies. Our results corroborate that the proposed algorithm can track the available capacity of the network despite changes in the demands of homes and other inelastic loads, improves a fairness metric, and increases the overall allocation to users who have a better reputation.
{"title":"Reputation-Based Fair Power Allocation to Plug-in Electric Vehicles in the Smart Grid","authors":"Abdullah Al Zishan, Moosa Moghimi Haji, Omid Ardakanian","doi":"10.1109/ICCPS48487.2020.00014","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00014","url":null,"abstract":"We present a reputation-based framework for allocating power to plug-in electric vehicles (EVs) in the smart grid. In this framework, the available capacity of the distribution network measured by distribution-level phasor measurement units is divided in a proportionally fair manner among connected EVs, considering their demands and self-declared deadlines. To encourage users to estimate their deadlines more precisely and conservatively, a weight is assigned to a each deadline based on the user’s reputation, which comprises two kinds of evidence: deadlines declared before and after the actual departure times in the recent past. Assuming reliable communication between sensors installed in the network and charging stations, we design a decentralized algorithm which allows the users to independently compute their fair share based on signals received from upstream sensors without sharing their private information, e.g., their deadline, with a central scheduler. We prove that this algorithm achieves quadratic convergence under specific conditions and evaluate it empirically on a test distribution network by comparing it with a centralized algorithm which solves the same optimization problem, a decentralized gradient-projection algorithm with linear convergence, and earliest-deadline-first and least-laxity-first scheduling policies. Our results corroborate that the proposed algorithm can track the available capacity of the network despite changes in the demands of homes and other inelastic loads, improves a fairness metric, and increases the overall allocation to users who have a better reputation.","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114675951","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}
Pub Date : 2020-04-01DOI: 10.1109/ICCPS48487.2020.00027
Anomadarshi Barua, Deepan Muthirayan, P. Khargonekar, M. A. Faruque
Micro-phasor measurement unit (μPMU) sensors in smart electric grids provide measurements of voltage and current at microsecond timescale across the network and have great potential value for grid diagnostics. In this work, we propose a novel neuro-cognitive inspired architecture based on Hierarchical Temporal Memory (HTM) for real-time anomaly detection in smart grid using μPMU data. The key technical idea is that the HTM learns a sparse distributed temporal representation of sequential data that turns out to be very useful for anomaly detection in real-time.Our numerical results show that the proposed HTM architecture can predict anomalies with 96%, 96%, and 98% accuracy for three different application profiles namely, Standard, Reward Few False Positive, Reward Few False Negative, respectively. The performance is compared with three state-of-the-art real-time anomaly detection algorithms and HTM demonstrates competitive score for real-time anomaly detection in μPMU data.
{"title":"Hierarchical Temporal Memory Based Machine Learning for Real-Time, Unsupervised Anomaly Detection in Smart Grid: WiP Abstract","authors":"Anomadarshi Barua, Deepan Muthirayan, P. Khargonekar, M. A. Faruque","doi":"10.1109/ICCPS48487.2020.00027","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00027","url":null,"abstract":"Micro-phasor measurement unit (μPMU) sensors in smart electric grids provide measurements of voltage and current at microsecond timescale across the network and have great potential value for grid diagnostics. In this work, we propose a novel neuro-cognitive inspired architecture based on Hierarchical Temporal Memory (HTM) for real-time anomaly detection in smart grid using μPMU data. The key technical idea is that the HTM learns a sparse distributed temporal representation of sequential data that turns out to be very useful for anomaly detection in real-time.Our numerical results show that the proposed HTM architecture can predict anomalies with 96%, 96%, and 98% accuracy for three different application profiles namely, Standard, Reward Few False Positive, Reward Few False Negative, respectively. The performance is compared with three state-of-the-art real-time anomaly detection algorithms and HTM demonstrates competitive score for real-time anomaly detection in μPMU data.","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121528100","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}
Pub Date : 2020-04-01DOI: 10.1109/iccps48487.2020.00005
{"title":"Foreword to the ICCPS 2020 Proceedings: Message from the Chairs","authors":"","doi":"10.1109/iccps48487.2020.00005","DOIUrl":"https://doi.org/10.1109/iccps48487.2020.00005","url":null,"abstract":"","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132989516","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}
Pub Date : 2020-04-01DOI: 10.1109/iccps48487.2020.00004
John Stankovic
Quickest Detection of Advanced Persistent Threats: A Semi-Markov Game Approach 9 Dinuka Sahabandu (University of Washington, Seattle, WA, USA), Joey Allen (Georgia Institute of Technology, Atlanta, GA, USA), Shana Moothedath (University of Washington, Seattle, WA, USA), Linda Bushnell (University of Washington, Seattle, WA, USA), Wenke Lee (Georgia Institute of Technology, Atlanta, GA, USA), and Radha Poovendran (University of Washington, Seattle, WA, USA)
{"title":"ICCPS 2020 TOC","authors":"John Stankovic","doi":"10.1109/iccps48487.2020.00004","DOIUrl":"https://doi.org/10.1109/iccps48487.2020.00004","url":null,"abstract":"Quickest Detection of Advanced Persistent Threats: A Semi-Markov Game Approach 9 Dinuka Sahabandu (University of Washington, Seattle, WA, USA), Joey Allen (Georgia Institute of Technology, Atlanta, GA, USA), Shana Moothedath (University of Washington, Seattle, WA, USA), Linda Bushnell (University of Washington, Seattle, WA, USA), Wenke Lee (Georgia Institute of Technology, Atlanta, GA, USA), and Radha Poovendran (University of Washington, Seattle, WA, USA)","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121922635","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}
Pub Date : 2020-04-01DOI: 10.1109/ICCPS48487.2020.00025
Xueli Fan, Qixin Wang, Jie Liu
In this work, we aim to propose a reliable automatic highway on-ramp smart vehicle merging protocol that tolerates arbitrary wireless packet losses, and guarantees the widely adopted safety rule of Constant Time Headway (CTH) [1] . This is different from the existing literature, which assumes reliable communications infrastructure (e.g. [2] ) or focuses on safety rules other than the CTH (e.g. [3] ).
{"title":"Work-in-Progress Abstract: A Reliable Wireless Smart Vehicle Highway On-Ramp Merging Protocol with Constant Time Headway Safety Guarantee","authors":"Xueli Fan, Qixin Wang, Jie Liu","doi":"10.1109/ICCPS48487.2020.00025","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00025","url":null,"abstract":"In this work, we aim to propose a reliable automatic highway on-ramp smart vehicle merging protocol that tolerates arbitrary wireless packet losses, and guarantees the widely adopted safety rule of Constant Time Headway (CTH) [1] . This is different from the existing literature, which assumes reliable communications infrastructure (e.g. [2] ) or focuses on safety rules other than the CTH (e.g. [3] ).","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122502177","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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