Pub Date : 2022-05-01DOI: 10.1109/iccps54341.2022.00016
Luyao Niu, D. Sahabandu, Andrew Clark, R. Poovendran
Resilient cyber-physical systems (CPS) must ensure safety and per-form required tasks in the presence of malicious cyber attacks. Recently, restart-based defenses have been proposed in which a CPS mitigates attacks by reverting to an initial safe state. In this paper, we consider a class of reactive restart approaches for CPS under malicious attacks with verifiable safety guarantees. We consider a setting where the controllers are engineered to crash and reboot following faults or attacks. We present a hybrid system model that captures the trade-off between security, availability, and safety of the CPS due to the reactive restart. We develop sufficient conditions under which an affine controller provides verifiable safety guar-antees for the physical plant using a barrier certificate approach. We synthesize safety-critical controllers using control barrier functions to guarantee system safety under given timing parameters. We present two case studies on the proposed approach using a warehouse temperature control system and a two-dimensional non-linear system. Our proposed approach guarantees the safety for both cases.
{"title":"Verifying Safety for Resilient Cyber-Physical Systems via Reactive Software Restart","authors":"Luyao Niu, D. Sahabandu, Andrew Clark, R. Poovendran","doi":"10.1109/iccps54341.2022.00016","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00016","url":null,"abstract":"Resilient cyber-physical systems (CPS) must ensure safety and per-form required tasks in the presence of malicious cyber attacks. Recently, restart-based defenses have been proposed in which a CPS mitigates attacks by reverting to an initial safe state. In this paper, we consider a class of reactive restart approaches for CPS under malicious attacks with verifiable safety guarantees. We consider a setting where the controllers are engineered to crash and reboot following faults or attacks. We present a hybrid system model that captures the trade-off between security, availability, and safety of the CPS due to the reactive restart. We develop sufficient conditions under which an affine controller provides verifiable safety guar-antees for the physical plant using a barrier certificate approach. We synthesize safety-critical controllers using control barrier functions to guarantee system safety under given timing parameters. We present two case studies on the proposed approach using a warehouse temperature control system and a two-dimensional non-linear system. Our proposed approach guarantees the safety for both cases.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120905322","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 : 2022-05-01DOI: 10.1109/iccps54341.2022.00006
{"title":"ICCPS 2022 Organizers","authors":"","doi":"10.1109/iccps54341.2022.00006","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00006","url":null,"abstract":"","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125450607","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 : 2022-05-01DOI: 10.1109/iccps54341.2022.00029
Brayden McDonald, F. Mueller
The increasing proliferation of cyber-physical systems in a multitude of applications presents a pressing need for effective methods of securing such devices. Many such systems are subject to tight timing constraints, which are poorly suited to traditional security methods due to the large runtime overhead and execution time variation introduced. However, the regular (and well documented) timing specifications of real-time systems open up new avenues with which such systems can be secured. This paper contributes T-SYS, a timed-system method of detecting intrusions into real-time systems via timing anomalies. A prototype implementation of T-SYS is integrated into a commercial real-time operating system (RTOS) in order to demonstrate its feasibility. Further, a compiler-based tool is developed to realize a T-SYS implementation with elastic timing bounds. This tool sup-ports integration of T-SYS protection into applications as well as the RTOS the kernel itself. Results on an ARM hardware platform with benchmark tasks including those drawn from an open-source UAV code base compare T-SYS with another method of timing-based intrusion detection and assess its effectiveness in terms of detecting attacks as they intrude a system.
{"title":"T-SYS: Timed-Based System Security for Real-Time Kernels","authors":"Brayden McDonald, F. Mueller","doi":"10.1109/iccps54341.2022.00029","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00029","url":null,"abstract":"The increasing proliferation of cyber-physical systems in a multitude of applications presents a pressing need for effective methods of securing such devices. Many such systems are subject to tight timing constraints, which are poorly suited to traditional security methods due to the large runtime overhead and execution time variation introduced. However, the regular (and well documented) timing specifications of real-time systems open up new avenues with which such systems can be secured. This paper contributes T-SYS, a timed-system method of detecting intrusions into real-time systems via timing anomalies. A prototype implementation of T-SYS is integrated into a commercial real-time operating system (RTOS) in order to demonstrate its feasibility. Further, a compiler-based tool is developed to realize a T-SYS implementation with elastic timing bounds. This tool sup-ports integration of T-SYS protection into applications as well as the RTOS the kernel itself. Results on an ARM hardware platform with benchmark tasks including those drawn from an open-source UAV code base compare T-SYS with another method of timing-based intrusion detection and assess its effectiveness in terms of detecting attacks as they intrude a system.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125455262","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 : 2022-05-01DOI: 10.1109/iccps54341.2022.00041
Wenqiang Chen, Ziqi Wang, Pengrui Quan, Zhencan Peng, Shupei Lin, M. Srivastava, J. Stankovic
Wearable devices like smartwatches and smart wristbands have gained substantial popularity in recent years. However, due to the limited size of the touch screens, smartwatches typically have a poor interactive experience for users. Recently, new technology has converted the human body into a virtual interface using finger activity induced vibrations. However, these solutions fail to meet expectations during real-world deployments, e.g., system performance significantly degrades due to human-based variations, such as hand shapes, tapping forces, and device positions. To mitigate these human-based variations, we collected a dataset of 114 users, built a deep-learning model, and designed a novel Siamese domain adversarial training algorithm. In this way, we implement a robust system which works at accuracy (97%) across different hand shapes, finger activity strengths, and smartwatch positions on the wrist. We have posted a demo video on YouTube (https://youtu.be/N5-ggvy2qfI).
{"title":"Making Vibration-based On-body Interaction Robust","authors":"Wenqiang Chen, Ziqi Wang, Pengrui Quan, Zhencan Peng, Shupei Lin, M. Srivastava, J. Stankovic","doi":"10.1109/iccps54341.2022.00041","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00041","url":null,"abstract":"Wearable devices like smartwatches and smart wristbands have gained substantial popularity in recent years. However, due to the limited size of the touch screens, smartwatches typically have a poor interactive experience for users. Recently, new technology has converted the human body into a virtual interface using finger activity induced vibrations. However, these solutions fail to meet expectations during real-world deployments, e.g., system performance significantly degrades due to human-based variations, such as hand shapes, tapping forces, and device positions. To mitigate these human-based variations, we collected a dataset of 114 users, built a deep-learning model, and designed a novel Siamese domain adversarial training algorithm. In this way, we implement a robust system which works at accuracy (97%) across different hand shapes, finger activity strengths, and smartwatch positions on the wrist. We have posted a demo video on YouTube (https://youtu.be/N5-ggvy2qfI).","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131833620","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 : 2022-05-01DOI: 10.1109/iccps54341.2022.00043
Emmanouil Samanis, Joseph Gardiner, A. Rashid
In the modern era, much of worldwide critical operations from a variety of different sectors are managed by industrial control systems (ICS). A typical ICS includes an extensive range of comput-erized devices, control systems, and networking appliances used to manage efficiently an industrial process across large geographical areas. ICS underpin sensitive and critical national infrastructures such as water treatment and energy production and transportation. The consequences of a successful attack against them can lead to shutting the infrastructure down which has major impacts such as production stoppages or safety implications for people, the environment, and assets. At the same time, running a process while the infrastructure is under attack or compromised also has safety im-plications, potentially catastrophic. This work-in-progress focuses on an adaptive approach, able to alter the defensive posture while providing assurances about operational capacity (or downgrading it) and safety. Our approach involves transforming policies from simply a means to enforce security requirements defined a priori, to adaptive objects that are capable to evolve in response to unfolding attacks. We use a case study of reconnaissance attacks and moving target defense as a means to realize such adaptive security policies.
{"title":"Adaptive Cyber Security for Critical Infrastructure","authors":"Emmanouil Samanis, Joseph Gardiner, A. Rashid","doi":"10.1109/iccps54341.2022.00043","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00043","url":null,"abstract":"In the modern era, much of worldwide critical operations from a variety of different sectors are managed by industrial control systems (ICS). A typical ICS includes an extensive range of comput-erized devices, control systems, and networking appliances used to manage efficiently an industrial process across large geographical areas. ICS underpin sensitive and critical national infrastructures such as water treatment and energy production and transportation. The consequences of a successful attack against them can lead to shutting the infrastructure down which has major impacts such as production stoppages or safety implications for people, the environment, and assets. At the same time, running a process while the infrastructure is under attack or compromised also has safety im-plications, potentially catastrophic. This work-in-progress focuses on an adaptive approach, able to alter the defensive posture while providing assurances about operational capacity (or downgrading it) and safety. Our approach involves transforming policies from simply a means to enforce security requirements defined a priori, to adaptive objects that are capable to evolve in response to unfolding attacks. We use a case study of reconnaissance attacks and moving target defense as a means to realize such adaptive security policies.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126428745","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 : 2022-05-01DOI: 10.1109/iccps54341.2022.00021
Ruihang Wang, Xinyi Zhang, Xiaoxia Zhou, Yonggang Wen, Rui Tan
Deep reinforcement learning (DRL) has shown good performance in tackling Markov decision process (MDP) problems. As DRL opti-mizes a long-term reward, it is a promising approach to improving the energy efficiency of data center cooling. However, enforcement of thermal safety constraint during DRL's state exploration is a main challenge. The widely adopted reward shaping approach adds negative reward when the exploratory action results in unsafety. Thus, it needs to experience sufficient unsafe states before it learns how to prevent unsafety. In this paper, we propose a safety-aware DRL framework for single-hall data center cooling control. It applies offline imitation learning and online post-hoc rectification to holis-tically prevent thermal unsafety during online DRL. In particular, the post-hoc rectification searches for the minimum modification to the DRL-recommended action such that the rectified action will not result in unsafety. The rectification is designed based on a thermal state transition model that is fitted using historical safe operation traces and able to extrapolate the transitions to unsafe states ex-plored by DRL. Extensive evaluation for chilled water and direct expansion cooled data centers in two climate conditions shows that our approach saves 22.7% to 26.6% total data center power compared with conventional control, reduces safety violations by 94.5% to 99% compared with reward shaping.
{"title":"Toward Physics-Guided Safe Deep Reinforcement Learning for Green Data Center Cooling Control","authors":"Ruihang Wang, Xinyi Zhang, Xiaoxia Zhou, Yonggang Wen, Rui Tan","doi":"10.1109/iccps54341.2022.00021","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00021","url":null,"abstract":"Deep reinforcement learning (DRL) has shown good performance in tackling Markov decision process (MDP) problems. As DRL opti-mizes a long-term reward, it is a promising approach to improving the energy efficiency of data center cooling. However, enforcement of thermal safety constraint during DRL's state exploration is a main challenge. The widely adopted reward shaping approach adds negative reward when the exploratory action results in unsafety. Thus, it needs to experience sufficient unsafe states before it learns how to prevent unsafety. In this paper, we propose a safety-aware DRL framework for single-hall data center cooling control. It applies offline imitation learning and online post-hoc rectification to holis-tically prevent thermal unsafety during online DRL. In particular, the post-hoc rectification searches for the minimum modification to the DRL-recommended action such that the rectified action will not result in unsafety. The rectification is designed based on a thermal state transition model that is fitted using historical safe operation traces and able to extrapolate the transitions to unsafe states ex-plored by DRL. Extensive evaluation for chilled water and direct expansion cooled data centers in two climate conditions shows that our approach saves 22.7% to 26.6% total data center power compared with conventional control, reduces safety violations by 94.5% to 99% compared with reward shaping.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124429045","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 : 2022-05-01DOI: 10.1109/iccps54341.2022.00028
Andrew Wintenberg, Matthew Blischke, S. Lafortune, N. Ozay
Obfuscation can be used by dynamic systems to ensure private and secure communication over networks vulnerable to eavesdroppers. Balancing the utility of sending information to intended recipients and privacy by hiding information from unintended recipients presents an interesting challenge. We propose a new framework for obfuscation that includes an inference interface to allow intended recipients to interpret obfuscated information. We model the security of the obfuscation with opacity, a formal notion of plausible deniability. Using techniques from distributed reactive synthesis, we show how to automatically design a privacy-enforcing obfuscator along with the inference interface that is given to intended recipients to use as a “key”. We demonstrate this approach by enforcing privacy while maintaining utility in a contact tracing model.
{"title":"A Dynamic Obfuscation Framework for Security and Utility","authors":"Andrew Wintenberg, Matthew Blischke, S. Lafortune, N. Ozay","doi":"10.1109/iccps54341.2022.00028","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00028","url":null,"abstract":"Obfuscation can be used by dynamic systems to ensure private and secure communication over networks vulnerable to eavesdroppers. Balancing the utility of sending information to intended recipients and privacy by hiding information from unintended recipients presents an interesting challenge. We propose a new framework for obfuscation that includes an inference interface to allow intended recipients to interpret obfuscated information. We model the security of the obfuscation with opacity, a formal notion of plausible deniability. Using techniques from distributed reactive synthesis, we show how to automatically design a privacy-enforcing obfuscator along with the inference interface that is given to intended recipients to use as a “key”. We demonstrate this approach by enforcing privacy while maintaining utility in a contact tracing model.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129528274","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 : 2022-05-01DOI: 10.1109/iccps54341.2022.00026
Md. Jaminur Islam, J. P. Talusan, Shameek Bhattacharjee, F. Tiausas, S. Vazirizade, Abhishek Dubey, K. Yasumoto, Sajal K. Das
Modern smart cities are focusing on smart transportation solutions to detect and mitigate the effects of various traffic incidents in the city. To materialize this, roadside units and ambient trans-portation sensors are being deployed to collect vehicular data that provides real-time traffic monitoring. In this paper, we first propose a real-time data-driven anomaly-based traffic incident detection framework for a city-scale smart transportation system. Specifically, we propose an incremental region growing approximation algorithm for optimal Spatio-temporal clustering of road segments and their data; such that road segments are strategically divided into highly correlated clusters. The highly correlated clusters enable identifying a Pythagorean Mean-based invariant as an anomaly detection metric that is highly stable under no incidents but shows a deviation in the presence of incidents. We learn the bounds of the invariants in a robust manner such that anomaly detection can generalize to unseen events, even when learning from real noisy data. We perform extensive experimental validation using mobility data collected from the City of Nashville, Tennessee, and prove that the method can detect incidents within each cluster in real-time.
{"title":"Anomaly based Incident Detection in Large Scale Smart Transportation Systems","authors":"Md. Jaminur Islam, J. P. Talusan, Shameek Bhattacharjee, F. Tiausas, S. Vazirizade, Abhishek Dubey, K. Yasumoto, Sajal K. Das","doi":"10.1109/iccps54341.2022.00026","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00026","url":null,"abstract":"Modern smart cities are focusing on smart transportation solutions to detect and mitigate the effects of various traffic incidents in the city. To materialize this, roadside units and ambient trans-portation sensors are being deployed to collect vehicular data that provides real-time traffic monitoring. In this paper, we first propose a real-time data-driven anomaly-based traffic incident detection framework for a city-scale smart transportation system. Specifically, we propose an incremental region growing approximation algorithm for optimal Spatio-temporal clustering of road segments and their data; such that road segments are strategically divided into highly correlated clusters. The highly correlated clusters enable identifying a Pythagorean Mean-based invariant as an anomaly detection metric that is highly stable under no incidents but shows a deviation in the presence of incidents. We learn the bounds of the invariants in a robust manner such that anomaly detection can generalize to unseen events, even when learning from real noisy data. We perform extensive experimental validation using mobility data collected from the City of Nashville, Tennessee, and prove that the method can detect incidents within each cluster in real-time.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133490901","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 : 2022-05-01DOI: 10.1109/iccps54341.2022.00035
Vlada Dementyeva, Cameron Hickert, Nicolas Sarfaraz, S. Zanlongo, Tamim I. Sookoor
The designers of safety-critical CPS that are intelligently automated using machine learning (ML) are encouraged to define invariants and utilize metrics to quantify the uncertainty of ML decisions in addition to focusing on the performance and functionality of the algorithm. Wheatman et al. [11] present Runtime Assurance for Distributed Intelligent Control Systems (RADICS) that extends the Simplex architecture [9] to provide runtime assurance for Cyber-Physical Systems (CPS) being controlled by machine learning al-gorithms. RADICS can thus allow designers to guarantee some minimum level of system performance via a safety controller while simultaneously allowing for greater average performance via an artificial intelligence (AI) controller. Existing implementations of RADICS have focused on simulated applications such as vehicular traffic control using the Simulation of Urban Mobility (SUMO) [5] and Flow [12] environments. The aim of this project is to implement RADICS in a physical environment in order to investigate and understand the limitations and challenges of physical deployments. We have selected a water treatment testbed as the application to conduct this evaluation. As a demonstration at ICCPS, we hope to use this testbed deployment to study the impact of real-world issues such as communication latencies, sensor failures, and incomplete information on the RADICS runtime assurance system. We also plan to extend the physical testbed into a hardware-in-the-loop smart city environment where the fidelity of the physical testbed will complement the scalability and flexibility of simulated components. This will allow further evaluation of assurance capabilities such as RADICS before they are deployed in the real world to ensure the safe and reliable operation of intelligent CPS. This work�s novel contributions include an extension of RADICS towards real-world use in cyber-physical systems, analysis of problems inherent to the shift to physical domains, and the introduction of an ensemble-like method for calculating confidence in the RADICS white box monitor.
{"title":"Runtime Assurance for Intelligent Cyber-Physical Systems","authors":"Vlada Dementyeva, Cameron Hickert, Nicolas Sarfaraz, S. Zanlongo, Tamim I. Sookoor","doi":"10.1109/iccps54341.2022.00035","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00035","url":null,"abstract":"The designers of safety-critical CPS that are intelligently automated using machine learning (ML) are encouraged to define invariants and utilize metrics to quantify the uncertainty of ML decisions in addition to focusing on the performance and functionality of the algorithm. Wheatman et al. [11] present Runtime Assurance for Distributed Intelligent Control Systems (RADICS) that extends the Simplex architecture [9] to provide runtime assurance for Cyber-Physical Systems (CPS) being controlled by machine learning al-gorithms. RADICS can thus allow designers to guarantee some minimum level of system performance via a safety controller while simultaneously allowing for greater average performance via an artificial intelligence (AI) controller. Existing implementations of RADICS have focused on simulated applications such as vehicular traffic control using the Simulation of Urban Mobility (SUMO) [5] and Flow [12] environments. The aim of this project is to implement RADICS in a physical environment in order to investigate and understand the limitations and challenges of physical deployments. We have selected a water treatment testbed as the application to conduct this evaluation. As a demonstration at ICCPS, we hope to use this testbed deployment to study the impact of real-world issues such as communication latencies, sensor failures, and incomplete information on the RADICS runtime assurance system. We also plan to extend the physical testbed into a hardware-in-the-loop smart city environment where the fidelity of the physical testbed will complement the scalability and flexibility of simulated components. This will allow further evaluation of assurance capabilities such as RADICS before they are deployed in the real world to ensure the safe and reliable operation of intelligent CPS. This work�s novel contributions include an extension of RADICS towards real-world use in cyber-physical systems, analysis of problems inherent to the shift to physical domains, and the introduction of an ensemble-like method for calculating confidence in the RADICS white box monitor.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121734450","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 : 2022-05-01DOI: 10.1109/iccps54341.2022.00025
F. Yang
In this paper, we present a system called Versatile Autonomous Racquet Sports Machine (VaRSM in short). VaRSM can play table tennis, tennis and badminton with respective racquets. There are two major challenges in building VaRSM: first, VaRSM must be able to strike and return balls of variable speed and power on fields of different size with diverse racquet motions; second, VaRSM must track and predict balls' fast trajectories and move its body in extremely short intervals of time. To address these challenges, we design several innovative technologies, which we group into the physical hardware module and the control software module. In the physical hardware module, we create a high speed swerve-drive platform and a high-flexibility racquet arm, using configurable integrated drive units. In the control software module, we develop a proactive progressive control method that takes advantage of the hardware's physical capabilities to achieve early ball trajectory prediction, quick striking decision-making, and fast yet stable machine motion. We build a prototype system based on these technologies. Our experiments demonstrate VaRSM is able to strike and return table tennis, tennis and badminton balls with high success rates and is capable of playing with human players. To our knowledge, VaRSM is the first machine able to play three different ball games, and may hold great significance in education, research, economy, and society.
{"title":"VaRSM: Versatile Autonomous Racquet Sports Machine","authors":"F. Yang","doi":"10.1109/iccps54341.2022.00025","DOIUrl":"https://doi.org/10.1109/iccps54341.2022.00025","url":null,"abstract":"In this paper, we present a system called Versatile Autonomous Racquet Sports Machine (VaRSM in short). VaRSM can play table tennis, tennis and badminton with respective racquets. There are two major challenges in building VaRSM: first, VaRSM must be able to strike and return balls of variable speed and power on fields of different size with diverse racquet motions; second, VaRSM must track and predict balls' fast trajectories and move its body in extremely short intervals of time. To address these challenges, we design several innovative technologies, which we group into the physical hardware module and the control software module. In the physical hardware module, we create a high speed swerve-drive platform and a high-flexibility racquet arm, using configurable integrated drive units. In the control software module, we develop a proactive progressive control method that takes advantage of the hardware's physical capabilities to achieve early ball trajectory prediction, quick striking decision-making, and fast yet stable machine motion. We build a prototype system based on these technologies. Our experiments demonstrate VaRSM is able to strike and return table tennis, tennis and badminton balls with high success rates and is capable of playing with human players. To our knowledge, VaRSM is the first machine able to play three different ball games, and may hold great significance in education, research, economy, and society.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121910054","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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