Pub Date : 2019-11-26DOI: 10.1109/ICCPS48487.2020.00021
Shilong Dai, Liang He, Xuebo Zhang
WiFi-based indoor localization has received extensive attentions from both academia and industry. However, the overhead of constructing and maintaining the WiFi fingerprint map remains a bottleneck for the wide-deployment of WiFi- based indoor localization systems. Recently, robots are adopted as the professional surveyor to fingerprint the environment autonomously. But the time and energy cost still limit the coverage of the robot surveyor, thus reduce its scalability.To fill this need, we design an Autonomous WiFi Fingerprinting system, called AuF, which autonomously constructs the fingerprint database with improved time and energy efficiency. AuF first conduct an automatic initialization process in the target indoor environment, then constructs the WiFi fingerprint database in two steps: (i) surveying the site without sojourn, (ii) recovering unreliable signals in the database with two methods. We have implemented and evaluated AuF using a Pioneer 3-DX robot, on two sites of our 70 × 90m2 Department building with different structures and deployments of access points (APs). The results show AuF finishes the fingerprint database construction in 43/51 minutes, and consumes 60/82 Wh on the two floors respectively, which is a 64%/71% and 61%/64% reduction when compared to traditional site survey methods, without degrading the localization accuracy.
{"title":"Autonomous WiFi Fingerprinting for Indoor Localization","authors":"Shilong Dai, Liang He, Xuebo Zhang","doi":"10.1109/ICCPS48487.2020.00021","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00021","url":null,"abstract":"WiFi-based indoor localization has received extensive attentions from both academia and industry. However, the overhead of constructing and maintaining the WiFi fingerprint map remains a bottleneck for the wide-deployment of WiFi- based indoor localization systems. Recently, robots are adopted as the professional surveyor to fingerprint the environment autonomously. But the time and energy cost still limit the coverage of the robot surveyor, thus reduce its scalability.To fill this need, we design an Autonomous WiFi Fingerprinting system, called AuF, which autonomously constructs the fingerprint database with improved time and energy efficiency. AuF first conduct an automatic initialization process in the target indoor environment, then constructs the WiFi fingerprint database in two steps: (i) surveying the site without sojourn, (ii) recovering unreliable signals in the database with two methods. We have implemented and evaluated AuF using a Pioneer 3-DX robot, on two sites of our 70 × 90m2 Department building with different structures and deployments of access points (APs). The results show AuF finishes the fingerprint database construction in 43/51 minutes, and consumes 60/82 Wh on the two floors respectively, which is a 64%/71% and 61%/64% reduction when compared to traditional site survey methods, without degrading the localization accuracy.","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132521421","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 : 2019-11-19DOI: 10.1109/ICCPS48487.2020.00031
Filip Klaesson, Petter Nilsson, A. Ames, R. Murray
Motivated by exploration of communication-constrained underground environments using robot teams, we study the problem of planning for intermittent connectivity in multi-agent systems. We propose a novel concept of information-consistency to handle situations where the plan is not initially known by all agents, and suggest an integer linear program for synthesizing information-consistent plans that also achieve auxiliary goals. Furthermore, inspired by network flow problems we propose a novel way to pose connectivity constraints that scales much better than previous methods. In the second part of the paper we apply these results in an exploration setting, and propose a clustering method that separates a large exploration problem into smaller problems that can be solved independently. We demonstrate how the resulting exploration algorithm is able to coordinate a team of ten agents to explore a large environment.
{"title":"Intermittent Connectivity for Exploration in Communication-Constrained Multi-Agent Systems","authors":"Filip Klaesson, Petter Nilsson, A. Ames, R. Murray","doi":"10.1109/ICCPS48487.2020.00031","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00031","url":null,"abstract":"Motivated by exploration of communication-constrained underground environments using robot teams, we study the problem of planning for intermittent connectivity in multi-agent systems. We propose a novel concept of information-consistency to handle situations where the plan is not initially known by all agents, and suggest an integer linear program for synthesizing information-consistent plans that also achieve auxiliary goals. Furthermore, inspired by network flow problems we propose a novel way to pose connectivity constraints that scales much better than previous methods. In the second part of the paper we apply these results in an exploration setting, and propose a clustering method that separates a large exploration problem into smaller problems that can be solved independently. We demonstrate how the resulting exploration algorithm is able to coordinate a team of ten agents to explore a large environment.","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117098368","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 : 2019-08-12DOI: 10.1109/ICCPS48487.2020.00008
F. Farokhi
We define discounted differential privacy, as an alternative to (conventional) differential privacy, to investigate privacy of evolving datasets, containing time series over an unbounded horizon. We use privacy loss as a measure of the amount of information leaked by the reports at a certain fixed time. We observe that privacy losses are weighted equally across time in the definition of differential privacy, and therefore the magnitude of privacy-preserving additive noise must grow without bound to ensure differential privacy over an infinite horizon. Motivated by the discounted utility theory within the economics literature, we use exponential and hyperbolic discounting of privacy losses across time to relax the definition of differential privacy under continual observations. This implies that privacy losses in distant past are less important than the current ones to an individual. We use discounted differential privacy to investigate privacy of evolving datasets using additive Laplace noise and show that the magnitude of the additive noise can remain bounded under discounted differential privacy. We illustrate the quality of privacy-preserving mechanisms satisfying discounted differential privacy on smart-meter measurement time-series of real households, made publicly available by Ausgrid (an Australian electricity distribution company).
{"title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","authors":"F. Farokhi","doi":"10.1109/ICCPS48487.2020.00008","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00008","url":null,"abstract":"We define discounted differential privacy, as an alternative to (conventional) differential privacy, to investigate privacy of evolving datasets, containing time series over an unbounded horizon. We use privacy loss as a measure of the amount of information leaked by the reports at a certain fixed time. We observe that privacy losses are weighted equally across time in the definition of differential privacy, and therefore the magnitude of privacy-preserving additive noise must grow without bound to ensure differential privacy over an infinite horizon. Motivated by the discounted utility theory within the economics literature, we use exponential and hyperbolic discounting of privacy losses across time to relax the definition of differential privacy under continual observations. This implies that privacy losses in distant past are less important than the current ones to an individual. We use discounted differential privacy to investigate privacy of evolving datasets using additive Laplace noise and show that the magnitude of the additive noise can remain bounded under discounted differential privacy. We illustrate the quality of privacy-preserving mechanisms satisfying discounted differential privacy on smart-meter measurement time-series of real households, made publicly available by Ausgrid (an Australian electricity distribution company).","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131889068","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 : 2019-08-06DOI: 10.1109/ICCPS48487.2020.00013
Meiyi Ma, E. Bartocci, Eli Lifland, J. Stankovic, Lu Feng
We present SaSTL—a novel Spatial Aggregation Signal Temporal Logic—for the efficient runtime monitoring of safety and performance requirements in smart cities. We first describe a study of over 1,000 smart city requirements, some of which can not be specified using existing logic such as Signal Temporal Logic (STL) and its variants. To tackle this limitation, we develop two new logical operators in SaSTL to augment STL for expressing spatial aggregation and spatial counting characteristics that are commonly found in real city requirements. We also develop efficient monitoring algorithms that can check a SaSTL requirement in parallel over multiple data streams (e.g., generated by multiple sensors distributed spatially in a city). We evaluate our SaSTL monitor by applying to two case studies with large-scale real city sensing data (e.g., up to 10,000 sensors in one requirement). The results show that SaSTL has a much higher coverage expressiveness than other spatial-temporal logics, and with a significant reduction of computation time for monitoring requirements. We also demonstrate that the SaSTL monitor can help improve the safety and performance of smart cities via simulated experiments.
{"title":"SaSTL: Spatial Aggregation Signal Temporal Logic for Runtime Monitoring in Smart Cities","authors":"Meiyi Ma, E. Bartocci, Eli Lifland, J. Stankovic, Lu Feng","doi":"10.1109/ICCPS48487.2020.00013","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00013","url":null,"abstract":"We present SaSTL—a novel Spatial Aggregation Signal Temporal Logic—for the efficient runtime monitoring of safety and performance requirements in smart cities. We first describe a study of over 1,000 smart city requirements, some of which can not be specified using existing logic such as Signal Temporal Logic (STL) and its variants. To tackle this limitation, we develop two new logical operators in SaSTL to augment STL for expressing spatial aggregation and spatial counting characteristics that are commonly found in real city requirements. We also develop efficient monitoring algorithms that can check a SaSTL requirement in parallel over multiple data streams (e.g., generated by multiple sensors distributed spatially in a city). We evaluate our SaSTL monitor by applying to two case studies with large-scale real city sensing data (e.g., up to 10,000 sensors in one requirement). The results show that SaSTL has a much higher coverage expressiveness than other spatial-temporal logics, and with a significant reduction of computation time for monitoring requirements. We also demonstrate that the SaSTL monitor can help improve the safety and performance of smart cities via simulated experiments.","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130740846","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 : 2018-12-20DOI: 10.1109/ICCPS48487.2020.00011
Sridhar Adepu, Ferdinand Brasser, Luis Garcia, Michael Rodler, Lucas Davi, A. Sadeghi, S. Zonouz
Cyber-physical control systems, such as industrial control systems (ICS), are increasingly targeted by cyberattacks. Such attacks can potentially cause tremendous damage, affect critical infrastructure or even jeopardize human life when the system does not behave as intended. Cyberattacks, however, are not new and decades of security research have developed plenty of solutions to thwart them. Unfortunately, many of these solutions cannot be easily applied to safety-critical cyber-physical systems. Further, the attack surface of ICS is quite different from what can be commonly assumed in classical IT systems.We present Scadman, a novel control-logic aware anomaly detection system for distributed cyber-physical systems. By observing the system-wide behavior, the correctness of individual controllers (like programmable logic controllers–PLCs) in ICS can be verified. This allows Scadman to detect a wide range of attacks, including malware attacks, code-reuse and dataonly attacks, as well as sensor attacks. We implemented and evaluated Scadman based on a real-world water treatment testbed for ICS security research and training. Our results show that we can detect a wide range of attacks–including attacks that have previously been undetectable by typical state estimation techniques–while causing no false-positive warning for nominal threshold values.
{"title":"Control Behavior Integrity for Distributed Cyber-Physical Systems","authors":"Sridhar Adepu, Ferdinand Brasser, Luis Garcia, Michael Rodler, Lucas Davi, A. Sadeghi, S. Zonouz","doi":"10.1109/ICCPS48487.2020.00011","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00011","url":null,"abstract":"Cyber-physical control systems, such as industrial control systems (ICS), are increasingly targeted by cyberattacks. Such attacks can potentially cause tremendous damage, affect critical infrastructure or even jeopardize human life when the system does not behave as intended. Cyberattacks, however, are not new and decades of security research have developed plenty of solutions to thwart them. Unfortunately, many of these solutions cannot be easily applied to safety-critical cyber-physical systems. Further, the attack surface of ICS is quite different from what can be commonly assumed in classical IT systems.We present Scadman, a novel control-logic aware anomaly detection system for distributed cyber-physical systems. By observing the system-wide behavior, the correctness of individual controllers (like programmable logic controllers–PLCs) in ICS can be verified. This allows Scadman to detect a wide range of attacks, including malware attacks, code-reuse and dataonly attacks, as well as sensor attacks. We implemented and evaluated Scadman based on a real-world water treatment testbed for ICS security research and training. Our results show that we can detect a wide range of attacks–including attacks that have previously been undetectable by typical state estimation techniques–while causing no false-positive warning for nominal threshold values.","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129281005","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 : 2017-11-01DOI: 10.1109/ICCPS48487.2020.00032
Amr Alanwar, Hazem Said, Ankur M. Mehta, M. Althoff
Distributed state estimation strongly depends on collaborative signal processing, which often requires excessive communication and computation to be executed on resource-constrained sensor nodes. To address this problem, we propose an event-triggered diffusion Kalman filter, which collects measurements and exchanges messages between nodes based on a local signal indicating the estimation error. On this basis, we develop an energy-aware state estimation algorithm that regulates the resource consumption in wireless networks and ensures the effectiveness of every consumed resource. The proposed algorithm does not require the nodes to share its local covariance matrices, and thereby allows considerably reducing the number of transmission messages. To confirm its efficiency, we apply the proposed algorithm to the distributed simultaneous localization and time synchronization problem and evaluate it on a physical testbed of a mobile quadrotor node and stationary custom ultra-wideband wireless devices. The obtained experimental results indicate that the proposed algorithm allows saving 86% of the communication overhead associated with the original diffusion Kalman filter while causing deterioration of performance by 16% only. We make the Matlab code and the real testing data available online1.
{"title":"Event-Triggered Diffusion Kalman Filters","authors":"Amr Alanwar, Hazem Said, Ankur M. Mehta, M. Althoff","doi":"10.1109/ICCPS48487.2020.00032","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00032","url":null,"abstract":"Distributed state estimation strongly depends on collaborative signal processing, which often requires excessive communication and computation to be executed on resource-constrained sensor nodes. To address this problem, we propose an event-triggered diffusion Kalman filter, which collects measurements and exchanges messages between nodes based on a local signal indicating the estimation error. On this basis, we develop an energy-aware state estimation algorithm that regulates the resource consumption in wireless networks and ensures the effectiveness of every consumed resource. The proposed algorithm does not require the nodes to share its local covariance matrices, and thereby allows considerably reducing the number of transmission messages. To confirm its efficiency, we apply the proposed algorithm to the distributed simultaneous localization and time synchronization problem and evaluate it on a physical testbed of a mobile quadrotor node and stationary custom ultra-wideband wireless devices. The obtained experimental results indicate that the proposed algorithm allows saving 86% of the communication overhead associated with the original diffusion Kalman filter while causing deterioration of performance by 16% only. We make the Matlab code and the real testing data available online1.","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128764115","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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