ACM Transactions on Cyber-Physical Systems最新文献

{"title":"Gordian","authors":"Matthew Weber, Baihong Jin, Gil Lederman, Yasser Shoukry, Edward A. Lee, S. Seshia, A. Sangiovanni-Vincentelli","doi":"10.1145/3386568","DOIUrl":"https://doi.org/10.1145/3386568","url":null,"abstract":"Accurate localization from Cyber-Physical Systems (CPS) is a critical enabling technology for context-aware applications and control. As localization plays an increasingly safety-critical role, location systems must be able to identify and eliminate faulty measurements to prevent dangerously inaccurate localization. In this article, we consider the range-based localization problem and propose a method to detect coordinated adversarial corruption on anchor positions and distance measurements. Our algorithm, Gordian, rapidly finds attacks by identifying geometric inconsistencies at the graph level without requiring assumptions about hardware, ranging mechanisms, or cryptographic protocols. We give necessary conditions for which attack detection is guaranteed to be successful in the noiseless case, and we use that intuition to extend Gordian to the noisy case where fewer guarantees are possible. In simulations generated from real-world sensor noise, we empirically show that Gordian’s trilateration counterexample generation procedure enables rapid attack detection even for combinatorially difficult problems.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":"15 1","pages":"1 - 27"},"PeriodicalIF":2.3,"publicationDate":"2020-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89094125","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":"Runtime Adaptation in Wireless Sensor Nodes Using Structured Learning","authors":"A. Sapio, S. Bhattacharyya, M. Wolf","doi":"10.1145/3372153","DOIUrl":"https://doi.org/10.1145/3372153","url":null,"abstract":"Markov Decision Processes (MDPs) provide important capabilities for facilitating the dynamic adaptation and self-optimization of cyber physical systems at runtime. In recent years, this has primarily taken the form of Reinforcement Learning (RL) techniques that eliminate some MDP components for the purpose of reducing computational requirements. In this work, we show that recent advancements in Compact MDP Models (CMMs) provide sufficient cause to question this trend when designing wireless sensor network nodes. In this work, a novel CMM-based approach to designing self-aware wireless sensor nodes is presented and compared to Q-Learning, a popular RL technique. We show that a certain class of CPS nodes is not well served by RL methods and contrast RL versus CMM methods in this context. Through both simulation and a prototype implementation, we demonstrate that CMM methods can provide significantly better runtime adaptation performance relative to Q-Learning, with comparable resource requirements.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":"4 1","pages":"1 - 28"},"PeriodicalIF":2.3,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3372153","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48069251","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":"CANOA: CAN Origin Authentication Through Power Side-Channel Monitoring","authors":"Shailja Thakur, Carlos Moreno, S. Fischmeister","doi":"10.1145/3571288","DOIUrl":"https://doi.org/10.1145/3571288","url":null,"abstract":"The lack of any sender authentication mechanism in place makes Controller Area Network (CAN) vulnerable to security threats. For instance, an attacker can impersonate an Electronic Control Unit (ECU) on the bus and send spoofed messages unobtrusively with the identifier of the impersonated ECU. To address this problem, we propose a novel source authentication technique that uses power consumption measurements of the ECU to authenticate the source of a message. A transmission of an ECU affects the power consumption and a characteristic pattern will appear. Our technique exploits the power consumption of each ECU during the transmission of a message to determine whether the message actually originated from the purported sender. We evaluate our approach in both a lab setup and a real vehicle. We also evaluate our approach against factors that can impact the power consumption measurement of the ECU. The results of the evaluation show that the proposed technique is applicable in a broad range of operating conditions with reasonable computational power requirements and attaining good accuracy.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2020-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49519523","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":"Anomaly Detection Based on RBM-LSTM Neural Network for CPS in Advanced Driver Assistance System","authors":"Di Wu, Hanlin Zhu, Yongxin Zhu, Victor I. Chang, Cong He, Ching‐Hsien Hsu, Hui Wang, Songlin Feng, Li Tian, Zunkai Huang","doi":"10.1145/3377408","DOIUrl":"https://doi.org/10.1145/3377408","url":null,"abstract":"Advanced Driver Assistance System (ADAS) is a typical Cyber Physical System (CPS) application for human–computer interaction. In the process of vehicle driving, we use the information from CPS on ADAS to not only help us understand the driving condition of the car but also help us change the driving strategies to drive in a better and safer way. After getting the information, the driver can evaluate the feedback information of the vehicle, so as to enhance the ability to assist in driving of the ADAS system. This completes a complete human–computer interaction process. However, the data obtained during the interaction usually form a large dimension, and irrelevant features sometimes hide the occurrence of anomalies, which poses a significant challenge to us to better understand the driving states of the car. To solve this problem, we propose an anomaly detection framework based on RBM-LSTM. In this hybrid framework, RBM is trained to extract general underlying features from data collected by CPS, and LSTM is trained from the features learned by RBM. This framework can effectively improve the prediction speed and present a good prediction accuracy to show vehicle driving condition. Besides, drivers are allowed to evaluate the prediction results, so as to improve the accuracy of prediction. Through the experimental results, we can find that the proposed framework not only simplifies the training of the entire neural network and increases the training speed but also greatly improves the accuracy of the interaction-driven data analysis. It is a valid method to analyze the data generated during the human interaction.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":"4 1","pages":"1 - 17"},"PeriodicalIF":2.3,"publicationDate":"2020-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3377408","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42822244","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":"A User-centric Security Solution for Internet of Things and Edge Convergence","authors":"PuthalDeepak, T. YangLaurence, DustdarSchahram, WenZhenyu, JunSong, MoorselAad van, RanjanRajiv","doi":"10.1145/3351882","DOIUrl":"https://doi.org/10.1145/3351882","url":null,"abstract":"The Internet of Things (IoT) is becoming a backbone of sensing infrastructure to several mission-critical applications such as smart health, disaster management, and smart cities. Due to resource-c...","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":"4 1","pages":"1-19"},"PeriodicalIF":2.3,"publicationDate":"2020-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3351882","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45195452","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":"System-level Logical Execution Time","authors":"Kai-Björn Gemlau, Leonie Köhler, R. Ernst, Sophie Quinton","doi":"10.1145/3381847","DOIUrl":"https://doi.org/10.1145/3381847","url":null,"abstract":"Logical Execution Time (LET) is a timed programming abstraction, which features predictable and composable timing. It has recently gained considerable attention in the automotive industry, where it was successfully applied to master the distribution of software applications on multi-core electronic control units. However, the LET abstraction in its conventional form is only valid within the scope of a single component. With the recent introduction of System-level Logical Execution Time (SL LET), the concept could be transferred to a system-wide scope. This article improves over a first paper on SL LET, by providing matured definitions and an extensive discussion of the concept. It also features a comprehensive evaluation exploring the impacts of SL LET with regard to design, verification, performance, and implementability. The evaluation goes far beyond the contexts in which LET was originally applied. Indeed, SL LET allows us to address many open challenges in the design and verification of complex embedded hardware/software systems addressing predictability, synchronization, composability, and extensibility. Furthermore, we investigate performance trade-offs, and we quantify implementation costs by providing an analysis of the additionally required buffers.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":" ","pages":"1 - 27"},"PeriodicalIF":2.3,"publicationDate":"2020-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3381847","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44853056","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":"Composable Finite State Machine-based Modeling for Quality-of-Information-aware Cyber-physical Systems","authors":"Rafael Rosales, M. Paulitsch","doi":"10.1145/3386244","DOIUrl":"https://doi.org/10.1145/3386244","url":null,"abstract":"Time plays a major role in the specification of Cyber-physical Systems (CPS) behavior with concurrency, timeliness, asynchrony, and resource limits as their main characteristics. In addition to timeliness, the specification of CPS needs to assess and unambiguously define its behavior with respect to the other Quality-of-Information (QoI) properties: (1) Correctness, (2) Completeness, (3) Consistency, and (4) Accuracy. Very often, CPS need to handle these QoI properties, and any combination thereof, multiple times when performing computation and communication processes. However, a model-driven and systematic approach to specify CPS behavior that jointly considers combined QoI aspects is possible but missing in existing methodologies. As the first contribution of this work, we provide an extension to an established model of computation (MoC) based on “Functions driven by Finite State Machine” (FunState) to enable a model-driven composition mechanism to create CPS behavior specifications from reusable components. Second, we present a novel set of design patterns to illustrate the modeling of QoI-aware CPS specifications that can be applied in several state-of-the-art Electronic System Level (ESL) methodologies. The time semantics of the MoC are formalized using the tagged-signal-model, and the presented model-driven approach enables the composition of multiple design patterns. The main benefits of the presented model-driven approach and design patterns to create CPS specifications are as follows: (a) reduce modeling effort, errors, and time through the reuse of known recipes to re-incurring tasks and allow to automatically generate repetitive control flows based on extended Finite State Machines; (b) increase system robustness and facilitate the creation of holistic QoI management allowing to unambiguously define system behavior for scenarios with single/multiple QoI requirement violations in different models of computation; (c) dynamically validate timing behavior of system implementations to enable a multi-objective optimization of nonfunctional properties that influence CPS timing. We demonstrate the aforementioned benefits through the modeling and evaluation of an infrastructure-assisted automated driving case study using Infrastructure-to-Vehicle (I2V) communications to distribute QoI critical road environment information.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":" ","pages":"1 - 27"},"PeriodicalIF":2.3,"publicationDate":"2020-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3386244","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44071573","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":"On Preserving Secrecy in Mobile Social Networks","authors":"Gabriela Suntaxi, A. A. E. Ghazi, Klemens Böhm","doi":"10.5445/IR/1000096955","DOIUrl":"https://doi.org/10.5445/IR/1000096955","url":null,"abstract":"Location-based services are one of the most important services offered by mobile social networks. Offering this kind of services requires accessing the physical position of users together with the access authorizations, i.e., who is authorized to access what information. However, these physical positions and authorizations are sensitive information which have to be kept secret from any adversary, including the service providers. As far as we know, the problem of offering location-based services in mobile social networks with a revocation feature under collusion assumption, i.e., an adversary colludes with the service provider, has not been studied. In this paper, we show how to solve this problem in the example of range queries. Specifically, we guarantee any adversary, including the service provider, is not able to learn (1) the physical position of the users, (2) the distance between his position and that of the users, and (3) whether two users are allowed to learn the distance between them. We propose two approaches namely two-layer symmetric encryption and two-layer attribute-based encryption. The main difference between the first and the second approach is that they use, among other encryption schemes, symmetric and attribute-based encryption, respectively. Next, we prove the secrecy guarantees of both approaches, analyze their complexity and provide experiments to evaluate their performance in practice.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":"1 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2020-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41976184","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":"A Multilabel Fuzzy Relevance Clustering System for Malware Attack Attribution in the Edge Layer of Cyber-Physical Networks","authors":"M. Alaeiyan, A. Dehghantanha, T. Dargahi, M. Conti, Saeed Parsa","doi":"10.1145/3351881","DOIUrl":"https://doi.org/10.1145/3351881","url":null,"abstract":"The rapid increase in the number of malicious programs has made malware forensics a daunting task and caused users’ systems to become in danger. Timely identification of malware characteristics including its origin and the malware sample family would significantly limit the potential damage of malware. This is a more profound risk in Cyber-Physical Systems (CPSs), where a malware attack may cause significant physical damage to the infrastructure. Due to limited on-device available memory and processing power in CPS devices, most of the efforts for protecting CPS networks are focused on the edge layer, where the majority of security mechanisms are deployed. Since the majority of advanced and sophisticated malware programs are combining features from different families, these malicious programs are not similar enough to any existing malware family and easily evade binary classifier detection. Therefore, in this article, we propose a novel multilabel fuzzy clustering system for malware attack attribution. Our system is deployed on the edge layer to provide insight into applicable malware threats to the CPS network. We leverage static analysis by utilizing Opcode frequencies as the feature space to classify malware families. We observed that a multilabel classifier does not classify a part of samples. We named this problem the instance coverage problem. To overcome this problem, we developed an ensemble-based multilabel fuzzy classification method to suggest the relevance of a malware instance to the stricken families. This classifier identified samples of VirusShare, RansomwareTracker, and BIG2015 with an accuracy of 94.66%, 94.26%, and 97.56%, respectively.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":"4 1","pages":"1 - 22"},"PeriodicalIF":2.3,"publicationDate":"2020-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3351881","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48730017","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":"UACFinder","authors":"Zhicheng Fu, Chunhui Guo, Zhenyu Zhang, Shangping Ren, L. Sha","doi":"10.1145/3375405","DOIUrl":"https://doi.org/10.1145/3375405","url":null,"abstract":"During the system development process, domain experts and developers often make assumptions about specifications and implementations. However, most of the assumptions being taken for granted by domain experts and developers are too tedious to be documented by them. When these unspecified assumptions are violated in an environment in which the system operates, failures can occur. According to the U.S. Food and Drug Administration (FDA) medical device recall database, medical device recalls caused by software failures are at an all-time high. One major cause of these recalls is violations of unspecified assumptions made in medical systems. Therefore, it is crucial to have tools to automatically identify such unspecified assumptions at an early stage of the systems development process to avoid fatal failures. In this article, we present a tool called Unspecified Assumption Carrier Finder (UACFinder) that uses data mining techniques to automatically identify potential syntactic carriers of unspecified assumptions in system design models. The main idea of this tool is based on the observation we obtained from our earlier analysis of software failures in medical device recalls caused by unspecified assumptions. We observed that unspecified assumptions often exist in medical systems through syntactic carriers, such as constant variables, frequently read/updated variables, and frequently executed action sequences. Therefore, we develop the UACFinder to automatically find these potential unspecified assumption syntactic carriers rather than unspecified assumptions themselves. Once the UACFinder identifies the potential unspecified assumption syntactic carriers, domain experts and developers can validate whether these syntactic carriers indeed carry unspecified assumptions. We use a simplified cardiac arrest treatment scenario as a case study to evaluate the UACFinder in mining potential syntactic carriers of unspecified assumptions. In addition, we invite a medical doctor to validate unspecified assumptions carried by the mined syntactic carriers. The case study demonstrates that the UACFinder is effective in helping to identify potential unspecified assumptions from system design models.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":" ","pages":"1 - 25"},"PeriodicalIF":2.3,"publicationDate":"2020-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3375405","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48838669","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}