ACM Transactions on Cyber-Physical Systems最新文献

{"title":"Toward a Scientific and Engineering Discipline of Cyber-Physical Systems","authors":"Chenyang Lu","doi":"10.1145/3464945","DOIUrl":"https://doi.org/10.1145/3464945","url":null,"abstract":"Cyber-physical systems (CPS) are driving a wide range of exciting applications from smart cities to smart healthcare. In contrast to traditional embedded systems, CPS operate in unpredictable environments in which they must meet stringent requirements such as end-to-end timeliness and physical system stability. The field of CPS addresses these critical challenges through seamless integration of computing and physical components. In the second decade since its inception as an interdisciplinary field, CPS is growing as a vibrant scientific and engineering discipline. I am honored to be named the new editor-in-chief of ACM Transactions on Cyber-Physical Systems (TCPS). TCPS has established itself as a leading journal in the field of CPS under the great leadership of Tei-Wei Kuo as the founding editor-in-chief. While traditional computer science disciplines are dominated by their premier conferences, the diverse and interdisciplinary nature of CPS provides a unique opportunity for TCPS to become the premier venue for publishing CPS research. Our aspiration is to grow TCPS into the flagship publication where best CPS works are published in a timely fashion, covering both the foundation and emergent frontiers of CPS research. In the following I’d like to share some initiatives that the editorial board is undertaking to realize our aspiration. Special issues on emerging topics. Special issues have been instrumental for establishing the topics and growing the submission pipeline of TCPS. Given the rapid evolution of CPS, we will continue to organize special issues on emerging topics. New topics on CPS often face challenges at established publication venues due to their interdisciplinary nature. TCPS aims to fill the gap with special issues that capture the state of the art of the new topics and shape the evolving areas. The success of special issues depends on the impacts of the topics and the leadership of the guest editors. We welcome strong proposals from the community on emerging topics of CPS. Foundation and core technologies. In parallel to the development of innovative applications and point solutions, we are witnessing the emergence of the foundation and core technologies of CPS as a scientific and engineering discipline. Examples range from cyber-physical co-design approaches to holistic system architectures crosscutting cyber and physical components. We welcome research papers on foundations and core CPS technologies underpinning the field of CPS. We will balance the special issues and regular issues to cover both new and established topics. Furthermore, some of the special issues will help evolve new topics toward established areas of CPS that continue to attract regular submissions. Timely, predictable, and rigorous reviews. Lengthy and unpredictable review cycles are major factors that discourage authors from submitting to journals. We aim to streamline the review process based on the best practices of ACM publications. Furthermore, we plan ","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3464945","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43575838","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}

{"title":"Hierarchical Planning for Dynamic Resource Allocation in Smart and Connected Communities","authors":"Geoffrey Pettet, Ayan Mukhopadhyay, Mykel J. Kochenderfer, A. Dubey","doi":"10.1145/3502869","DOIUrl":"https://doi.org/10.1145/3502869","url":null,"abstract":"Resource allocation under uncertainty is a classic problem in city-scale cyber-physical systems. Consider emergency response, where urban planners and first responders optimize the location of ambulances to minimize expected response times to incidents such as road accidents. Typically, such problems involve sequential decision making under uncertainty and can be modeled as Markov (or semi-Markov) decision processes. The goal of the decision maker is to learn a mapping from states to actions that can maximize expected rewards. While online, offline, and decentralized approaches have been proposed to tackle such problems, scalability remains a challenge for real world use cases. We present a general approach to hierarchical planning that leverages structure in city level CPS problems for resource allocation. We use emergency response as a case study and show how a large resource allocation problem can be split into smaller problems. We then use Monte Carlo planning for solving the smaller problems and managing the interaction between them. Finally, we use data from Nashville, Tennessee, a major metropolitan area in the United States, to validate our approach. Our experiments show that the proposed approach outperforms state-of-the-art approaches used in the field of emergency response.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46520928","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}

{"title":"Using Machine Learning for Dependable Outlier Detection in Environmental Monitoring Systems","authors":"Gonçalo Jesus, A. Casimiro, Anabela Oliveira","doi":"10.1145/3445812","DOIUrl":"https://doi.org/10.1145/3445812","url":null,"abstract":"Sensor platforms used in environmental monitoring applications are often subject to harsh environmental conditions while monitoring complex phenomena. Therefore, designing dependable monitoring systems is challenging given the external disturbances affecting sensor measurements. Even the apparently simple task of outlier detection in sensor data becomes a hard problem, amplified by the difficulty in distinguishing true data errors due to sensor faults from deviations due to natural phenomenon, which look like data errors. Existing solutions for runtime outlier detection typically assume that the physical processes can be accurately modeled, or that outliers consist in large deviations that are easily detected and filtered by appropriate thresholds. Other solutions assume that it is possible to deploy multiple sensors providing redundant data to support voting-based techniques. In this article, we propose a new methodology for dependable runtime detection of outliers in environmental monitoring systems, aiming to increase data quality by treating them. We propose the use of machine learning techniques to model each sensor behavior, exploiting the existence of correlated data provided by other related sensors. Using these models, along with knowledge of processed past measurements, it is possible to obtain accurate estimations of the observed environment parameters and build failure detectors that use these estimations. When a failure is detected, these estimations also allow one to correct the erroneous measurements and hence improve the overall data quality. Our methodology not only allows one to distinguish truly abnormal measurements from deviations due to complex natural phenomena, but also allows the quantification of each measurement quality, which is relevant from a dependability perspective. We apply the methodology to real datasets from a complex aquatic monitoring system, measuring temperature and salinity parameters, through which we illustrate the process for building the machine learning prediction models using a technique based on Artificial Neural Networks, denoted ANNODE (ANN Outlier Detection). From this application, we also observe the effectiveness of our ANNODE approach for accurate outlier detection in harsh environments. Then we validate these positive results by comparing ANNODE with state-of-the-art solutions for outlier detection. The results show that ANNODE improves existing solutions regarding accuracy of outlier detection.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3445812","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45316508","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}

{"title":"Analysing Mission-critical Cyber-physical Systems with AND/OR Graphs and MaxSAT","authors":"Martín Barrère, C. Hankin","doi":"10.1145/3451169","DOIUrl":"https://doi.org/10.1145/3451169","url":null,"abstract":"Cyber-Physical Systems (CPS) often involve complex networks of interconnected software and hardware components that are logically combined to achieve a common goal or mission; for example, keeping a plane in the air or providing energy to a city. Failures in these components may jeopardise the mission of the system. Therefore, identifying the minimal set of critical CPS components that is most likely to fail, and prevent the global system from accomplishing its mission, becomes essential to ensure reliability. In this article, we present a novel approach to identifying the Most Likely Mission-critical Component Set (MLMCS) using AND/OR dependency graphs enriched with independent failure probabilities. We address the MLMCS problem as a Maximum Satisfiability (MaxSAT) problem. We translate probabilities into a negative logarithmic space to linearise the problem within MaxSAT. The experimental results conducted with our open source tool LDA4CPS indicate that the approach is both effective and efficient. We also present a case study on complex aircraft systems that shows the feasibility of our approach and its applicability to mission-critical cyber-physical systems. Finally, we present two MLMCS-based security applications focused on system hardening and forensic investigations.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3451169","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47080722","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}

{"title":"EVScout2.0: Electric Vehicle Profiling Through Charging Profile","authors":"Alessandro Brighente, M. Conti, Denis Donadel, F. Turrin","doi":"10.1145/3565268","DOIUrl":"https://doi.org/10.1145/3565268","url":null,"abstract":"Electric Vehicles (EVs) represent a green alternative to traditional fuel-powered vehicles. To enforce their widespread use, both the technical development and the security of users shall be guaranteed. Users’ privacy represents a possible threat that impairs the adoption of EVs. In particular, recent works showed the feasibility of identifying EVs based on the current exchanged during the charging phase. In fact, while the resource negotiation phase runs over secure communication protocols, the signal exchanged during the actual charging contains features peculiar to each EV. In what is commonly known as profiling, a suitable feature extractor can associate such features to each EV. In this paper, we propose EVScout2.0, an extended and improved version of our previously proposed framework to profile EVs based on their charging behavior. By exploiting the current and pilot signals exchanged during the charging phase, our scheme can extract features peculiar for each EV, hence allowing their profiling. We implemented and tested EVScout2.0 over a set of real-world measurements considering over 7500 charging sessions from a total of 137 EVs. In particular, numerical results show the superiority of EVScout2.0 with respect to the previous version. EVScout2.0 can profile EVs, attaining a maximum of 0.88 for both recall and precision scores in the case of a balanced dataset. To the best of the authors’ knowledge, these results set a new benchmark for upcoming privacy research for large datasets of EVs.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47795077","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}

{"title":"TPrune","authors":"Jiachen Mao, Huanrui Yang, Ang Li, H. Li, Yiran Chen","doi":"10.1145/3446640","DOIUrl":"https://doi.org/10.1145/3446640","url":null,"abstract":"The invention of Transformer model structure boosts the performance of Neural Machine Translation (NMT) tasks to an unprecedented level. Many previous works have been done to make the Transformer model more execution-friendly on resource-constrained platforms. These researches can be categorized into three key fields: Model Pruning, Transfer Learning, and Efficient Transformer Variants. The family of model pruning methods are popular for their simplicity in practice and promising compression rate and have achieved great success in the field of convolution neural networks (CNNs) for many vision tasks. Nonetheless, previous Transformer pruning works did not perform a thorough model analysis and evaluation on each Transformer component on off-the-shelf mobile devices. In this work, we analyze and prune transformer models at the line-wise granularity and also implement our pruning method on real mobile platforms. We explore the properties of all Transformer components as well as their sparsity features, which are leveraged to guide Transformer model pruning. We name our whole Transformer analysis and pruning pipeline as TPrune. In TPrune, we first propose Block-wise Structured Sparsity Learning (BSSL) to analyze Transformer model property. Then, based on the characters derived from BSSL, we apply Structured Hoyer Square (SHS) to derive the final pruned models. Comparing with the state-of-the-art Transformer pruning methods, TPrune is able to achieve a higher model compression rate with less performance degradation. Experimental results show that our pruned models achieve 1.16×–1.92× speedup on mobile devices with 0%–8% BLEU score degradation compared with the original Transformer model.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3446640","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64037610","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}

{"title":"BloothAir","authors":"Kai Li, N. Lu, Jingjing Zheng, Pei Zhang, Wei Ni, E. Tovar","doi":"10.1145/3448254","DOIUrl":"https://doi.org/10.1145/3448254","url":null,"abstract":"Thanks to flexible deployment and excellent maneuverability, autonomous drones have been recently considered as an effective means to act as aerial data relays for wireless ground devices with limited or no cellular infrastructure, e.g., smart farming in a remote area. Due to the broadcast nature of wireless channels, data communications between the drones and the ground devices are vulnerable to eavesdropping attacks. This article develops BloothAir, which is a secure multi-hop aerial relay system based on Bluetooth Low Energy (BLE) connected autonomous drones. For encrypting the BLE communications in BloothAir, a channel-based secret key generation is proposed, where received signal strength at the drones and the ground devices is quantized to generate the secret keys. Moreover, a dynamic programming-based channel quantization scheme is studied to minimize the secret key bit mismatch rate of the drones and the ground devices by recursively adjusting the quantization intervals. To validate the design of BloothAir, we build a multi-hop aerial relay testbed by using the MX400 drone platform and the Gust radio transceiver, which is a new lightweight onboard BLE communicator specially developed for the drone. Extensive real-world experiments demonstrate that the BloothAir system achieves a significantly lower secret key bit mismatch rate than the key generation benchmarks, which use the static quantization intervals. In addition, the high randomness of the generated secret keys is verified by the standard NIST test, thereby effectively protecting the BLE communications in BloothAir from the eavesdropping attacks.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90655146","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}

{"title":"RIDS","authors":"Pierre-François Gimenez, Jonathan Roux, E. Alata, G. Auriol, M. Kaâniche, V. Nicomette","doi":"10.1145/3441458","DOIUrl":"https://doi.org/10.1145/3441458","url":null,"abstract":"The expansion of the Internet-of-Things (IoT) market is visible in homes, factories, public places, and smart cities. While the massive deployment of connected devices offers opportunities to improve quality of life and to develop new services, the impact of such devices on the security of the users in a context where the level of malicious threat continues to increase is a major concern. One of the challenges is the heterogeneity and constant evolution of wireless technologies and protocols used. To overcome this problem, we propose RIDS, a Radio Intrusion Detection System that is based on the monitoring and profiling of radio communications at the physical layer level using autoencoder neural networks. RIDS is independent of the wireless protocols and modulation technologies used. Besides, it is designed to provide a threefold diagnosis of the detected anomalies: temporal (start and end date of the detected anomaly), frequential (main frequency of the anomaly), and spatial (location of the origin of the anomaly). To demonstrate the relevance and the efficiency of our approach, we collected a large dataset of radio-communications recorded with three different probes deployed in an experimental room. Multiple real-world attacks involving a wide variety of communication technologies are also injected to assess the detection and diagnosis efficiency. The results demonstrate the efficiency of RIDS in detecting and diagnosing anomalies that occurred in the 400–500 Mhz and 800–900 Mhz frequency bands. It is noteworthy that compromised devices and attacks using these communication bands are generally not easily covered by traditional solutions.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81335073","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}

{"title":"Characterization of Link Quality Fluctuation in Mobile Wireless Sensor Networks","authors":"Jianjun Wen, W. Dargie","doi":"10.1145/3448737","DOIUrl":"https://doi.org/10.1145/3448737","url":null,"abstract":"Wireless sensor networks accommodating the mobility of nodes will play important roles in the future. In residential, rehabilitation, and clinical settings, sensor nodes can be attached to the body of a patient for long-term and uninterrupted monitoring of vital biomedical signals. Likewise, in industrial settings, workers as well as mobile robots can carry sensor nodes to augment their perception and to seamlessly interact with their environments. Nevertheless, such applications require reliable communications as well as high throughput. Considering the primary design goals of the sensing platforms (low-power, affordable cost, large-scale deployment, longevity, operating in the ISM band), maintaining reliable links is a formidable challenge. This challenge can partially be alleviated if the nature of link quality fluctuation can be known or estimated on time. Indeed, higher-level protocols such as handover and routing protocols rely on knowledge of link quality fluctuation to seamlessly transfer communication to alternative routes when the quality of existing routes deteriorates. In this article, we present the result of extensive experimental study to characterise link quality fluctuation in mobile environments. The study focuses on slow movements (<5 km h-1) signifying the movement of people and robots and transceivers complying to the IEEE 802.15.4 specification. Hence, we deployed mobile robots that interact with strategically placed stationary relay nodes. Our study considered different types of link quality characterisation metrics that provide complementary and useful insights. To demonstrate the usefulness of our experiments and observations, we implemented a link quality estimation technique using a Kalman Filter. To set up the model, we employed two link quality metrics along with the statistics we established during our experiments. The article will compare the performance of four proposed approaches with ours.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3448737","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45561528","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}

{"title":"Metagames and Hypergames for Deception-Robust Control","authors":"Craig Bakker, Arnab Bhattacharya, S. Chatterjee, D. Vrabie","doi":"10.1145/3439430","DOIUrl":"https://doi.org/10.1145/3439430","url":null,"abstract":"Increasing connectivity to the Internet for remote monitoring and control has made cyber-physical systems more vulnerable to deliberate attacks; purely cyber attacks can thereby have physical consequences. Long-term, stealthy attacks such as Stuxnet can be described as Advanced Persistent Threats (APTs). Here, we extend our previous work on hypergames and APTs to develop hypergame-based defender strategies that are robust to deception and do not rely on attack detection. These strategies provide provable bounds—and provably optimal bounds—on the attacker payoff. Strategies based on Bayesian priors do not provide such bounds. We then numerically demonstrate our approach on a building control subsystem and discuss next steps in extending this approach toward an operational capability.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3439430","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44719075","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}