Yasser Shoukry, Shaunak Mishra, Zutian Luo, S. Diggavi
{"title":"Sybil Attack Resilient Traffic Networks: A Physics-Based Trust Propagation Approach","authors":"Yasser Shoukry, Shaunak Mishra, Zutian Luo, S. Diggavi","doi":"10.1109/ICCPS.2018.00013","DOIUrl":"https://doi.org/10.1109/ICCPS.2018.00013","url":null,"abstract":"We study a crowdsourcing aided road traffic estimation setup, where a fraction of users (vehicles) are malicious, and report wrong sensory information, or even worse, report the presence of Sybil (ghost) vehicles that do not physically exist. The motivation for such attacks lies in the possibility of creating a \"virtual\" congestion that can influence routing algorithms, leading to \"actual\" congestion and chaos. We propose a Sybil attack-resilient traffic estimation and routing algorithm that is resilient against such attacks. In particular, our algorithm leverages noisy information from legacy sensing infrastructure, along with the dynamics and proximity graph of vehicles inferred from crowdsourced data. Furthermore, the scalability of our algorithm is based on efficient Boolean Satisfiability (SAT) solvers. We validated our algorithm using real traffic data from the Italian city of Bologna. Our algorithm led to a significant reduction in average travel time in the presence of Sybil attacks, including cases where the travel time was reduced from about an hour to a few minutes.","PeriodicalId":199062,"journal":{"name":"2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124940160","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":"CityResolver: A Decision Support System for Conflict Resolution in Smart Cities","authors":"Meiyi Ma, J. Stankovic, Lu Feng","doi":"10.1109/ICCPS.2018.00014","DOIUrl":"https://doi.org/10.1109/ICCPS.2018.00014","url":null,"abstract":"Resolution of conflicts across services in smart cities is an important yet challenging problem. We present CityResolver – a decision support system for conflict resolution in smart cities. CityResolver uses an Integer Linear Programming based method to generate a small set of resolution options, and a Signal Temporal Logic based verification approach to compute these resolution options' impact on city performance. The trade-offs between resolution options are shown in a dashboard to support decision makers in selecting the best resolution. We demonstrate the effectiveness of CityResolver by comparing the performance with two baselines: a smart city without conflict resolution, and CityGuard which uses a priority rule-based conflict resolution. Experimental results show that CityResolver can reduce the number of requirement violations and improve the city performance significantly.","PeriodicalId":199062,"journal":{"name":"2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)","volume":"463 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122147285","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":"Co-Regulation of Computational and Physical Effectors in a Quadrotor Unmanned Aircraft System","authors":"Xinkai Zhang, Seth Doebbeling, Justin M. Bradley","doi":"10.1109/ICCPS.2018.00020","DOIUrl":"https://doi.org/10.1109/ICCPS.2018.00020","url":null,"abstract":"Traditional control strategies rely on real-time computer tasks executing in fixed intervals providing periodic sampling upon which discrete controllers are designed. But emerging trends challenge this fixed resource allocation strategy by sampling at the \"right\" time rather than at fixed intervals. We propose a strategy in which a model representing the sampling rate is augmented to the state-space model of a quadrotor unmanned aircraft system, coupled controllers are designed for this holistic system, and computational and physical effectors are co-regulated in response to system performance. We investigate a new discrete-time-varying control strategy by gain scheduling a discrete linear quadratic regulator controller at a series of sampling rates, and co-regulating the sampling rates using a cyber controller whose gains are optimized via a strategic cost function. We then show step responses of the quadrotor to demonstrate how rapid changes in physical system gain at discrete sampling rates negatively impacts system performance. To solve this we introduce a new cyber control strategy that reduces these negative impacts and show how the response can be improved. Since most multicopters employ waypoint tracking planning and guidance, we also evaluate our strategy by assessing performance of the quadrotor in following a waypoint trajectory giving a much better indication of how a control strategy affects mission performance. We develop cyber-physical metrics for assessing waypoint following performance and use them to improve controller design. Results show that our proposed coupled cyber-physical system model and controller can provide physical system performance similar to fixed-rate optimal control strategies but with less control effort and much less computational utilization. Our strategy allows cyber and physical resources to be dynamically allocated to system demands as needed.","PeriodicalId":199062,"journal":{"name":"2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122664774","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":"Towards a Green and Secure Architecture for Reconfigurable IoT End-Devices","authors":"Daniel Oliveira, T. Gomes, S. Pinto","doi":"10.1109/ICCPS.2018.00041","DOIUrl":"https://doi.org/10.1109/ICCPS.2018.00041","url":null,"abstract":"With the advent of the Internet of Things (IoT), objects are becoming smaller, smarter and increasingly connected. IoT devices are being deployed in massive numbers, and the success of this new Internet era is heavily dependent upon the trust and security built over billions of heterogeneous devices. However, securing IoT devices can be a quandary, with hardware requirements, energy consumption and cost limitations pulling in opposite directions. This work-in-progress proposes a novel architecture for reconfigurable IoT end-devices, where several constrains, such as the security, performance and power budget must be seriously considered. The proposed architecture intends to go beyond state-of-the-art by focusing on a trade-off between device security and power consumption, in an attempt to find an optimal design point in the energy-security space.","PeriodicalId":199062,"journal":{"name":"2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126606337","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":"Distributed Optimal Control Synthesis for Multi-Robot Systems under Global Temporal Tasks","authors":"Y. Kantaros, M. Zavlanos","doi":"10.1109/ICCPS.2018.00024","DOIUrl":"https://doi.org/10.1109/ICCPS.2018.00024","url":null,"abstract":"This paper proposes a distributed sampling-based algorithm for optimal multi-robot control synthesis under global Linear Temporal Logic (LTL) formulas. Existing planning approaches under global temporal goals rely on graph search techniques applied to a synchronous product automaton constructed among the robots. In our previous work, we have proposed a more tractable centralized sampling-based algorithm that builds incrementally trees that approximate the state-space and transitions of the synchronous product automaton and does not require sophisticated graph search techniques. In this work, we provide a distributed implementation of this sampling-based algorithm, whereby the robots collaborate to build subtrees that decreases the computational time significantly. We provide theoretical guarantees showing that the distributed algorithm preserves the probabilistic completeness and asymptotic optimality of its centralized counterpart. To the best of our knowledge, this is the first distributed, computationally efficient, probabilistically complete, and asymptotically optimal control synthesis algorithm for multi-robot systems under global temporal tasks.","PeriodicalId":199062,"journal":{"name":"2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)","volume":"39 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125735883","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}
Fanxin Kong, Meng Xu, James Weimer, O. Sokolsky, Insup Lee
{"title":"Cyber-Physical System Checkpointing and Recovery","authors":"Fanxin Kong, Meng Xu, James Weimer, O. Sokolsky, Insup Lee","doi":"10.1109/ICCPS.2018.00011","DOIUrl":"https://doi.org/10.1109/ICCPS.2018.00011","url":null,"abstract":"Transitioning to more open architectures has been making Cyber-Physical Systems (CPS) vulnerable to malicious attacks that are beyond the conventional cyber attacks. This paper studies attack-resilience enhancement for a system under emerging attacks in the environment of the controller. An effective way to address this problem is to make system state estimation accurate enough for control regardless of the compromised components. This work follows this way and develops a procedure named CPS checkpointing and recovery, which leverages historical data to recover failed system states. Specially, we first propose a new concept of physical-state recovery. The essential operation is defined as rolling the system forward starting from a consistent historical system state. Second, we design a checkpointing protocol that defines how to record system states for the recovery. The protocol introduces a sliding window that accommodates attack-detection delay to improve the correctness of stored states. Third, we present a use case of CPS checkpointing and recovery that deals with compromised sensor measurements. At last, we evaluate our design through conducting simulator-based experiments and illustrating the use of our design with an unmanned vehicle case study.","PeriodicalId":199062,"journal":{"name":"2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123171250","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}
S. Preum, Sile Shu, Jonathan Ting, Vincent Lin, Ronald D. Williams, J. Stankovic, H. Alemzadeh
{"title":"Towards a Cognitive Assistant System for Emergency Response","authors":"S. Preum, Sile Shu, Jonathan Ting, Vincent Lin, Ronald D. Williams, J. Stankovic, H. Alemzadeh","doi":"10.1109/ICCPS.2018.00047","DOIUrl":"https://doi.org/10.1109/ICCPS.2018.00047","url":null,"abstract":"This abstract presents our preliminary results on development of a cognitive assistant system for emergency response that aims to improve situational awareness and safety of first responders. This system integrates a suite of smart wearable sensors, devices, and analytics for real-time collection and analysis of in-situ data from incident scene and providing dynamic data-driven insights to responders on the most effective response actions to take.","PeriodicalId":199062,"journal":{"name":"2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127164092","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}
Matt Schmittle, Anna Lukina, L. Vacek, J. Das, C. V. Buskirk, Stephen A. Rees, J. Sztipanovits, R. Grosu, Vijay R. Kumar
{"title":"OpenUAV: A UAV Testbed for the CPS and Robotics Community","authors":"Matt Schmittle, Anna Lukina, L. Vacek, J. Das, C. V. Buskirk, Stephen A. Rees, J. Sztipanovits, R. Grosu, Vijay R. Kumar","doi":"10.1109/ICCPS.2018.00021","DOIUrl":"https://doi.org/10.1109/ICCPS.2018.00021","url":null,"abstract":"Multirotor Unmanned Aerial Vehicles (UAV) have grown in popularity for research and education, overcoming challenges associated with fixed wing and ground robots. Unfortunately, extensive physical testing can be expensive and time consuming because of short flight times due to battery constraints and safety precautions. Simulation tools offer a low barrier to entry and enable testing and validation before field trials. However, most of the well-known simulators today have a high barrier to entry due to the need for powerful computers and the time required for initial set up. In this paper, we present OpenUAV, an open source test bed for UAV education and research that overcomes these barriers. We leverage the Containers as a Service (CaaS) technology to enable students and researchers carry out simulations on the cloud. We have based our framework on open-source tools including ROS, Gazebo, Docker, PX4, and Ansible, we designed the simulation framework so that it has no special hardware requirements. Two use-cases are presented. First, we show how a UAV can navigate around obstacles, and second, we test a multi-UAV swarm formation algorithm. To our knowledge, this is the first open-source, cloud-enabled testbed for UAVs. The code is available on GitHub: https://github.com/Open-UAV.","PeriodicalId":199062,"journal":{"name":"2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114825891","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}
Kai Li, Harrison Kurunathan, Ricardo Severino, E. Tovar
{"title":"Cooperative Key Generation for Data Dissemination in Cyber-Physical Systems","authors":"Kai Li, Harrison Kurunathan, Ricardo Severino, E. Tovar","doi":"10.1109/ICCPS.2018.00039","DOIUrl":"https://doi.org/10.1109/ICCPS.2018.00039","url":null,"abstract":"Securing wireless communication is significant for privacy and confidentiality of sensing data in Cyber-Physical Systems (CPS). However, due to broadcast nature of radio channels, disseminating sensory data is vulnerable to eavesdropping and message modification. Generating secret keys by extracting the shared randomness in a wireless fading channel is a promising way to improve the communication security. In this poster, we present a novel secret key generation protocol for securing real-time data dissemination in CPS, where the sensor nodes cooperatively generate a shared key by estimating the quantized fading channel randomness. A 2-hop wireless sensor network testbed is built and preliminary experimental results show that the quantization intervals and distance between the nodes lead to a secret bit mismatch.","PeriodicalId":199062,"journal":{"name":"2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133747383","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":"Predicting Malicious Intention in CPS under Cyber-Attack","authors":"N. Bezzo","doi":"10.1109/ICCPS.2018.00049","DOIUrl":"https://doi.org/10.1109/ICCPS.2018.00049","url":null,"abstract":"Modern autonomous cyber-physical systems (CPS) have been demonstrated to be vulnerable to cyber-attacks like sensor spoofing in which an attacker compromises sensor readings while remaining stealthy to hijack the system toward undesired states. The majority of security techniques developed today are, however, reactive and concerned with detection and interdiction of attacks without considering predicting the intention of the attack. To deal with such problem, we propose a Reachability-based approach and a Bayesian Inverse Reinforcement Learning technique that leverages the history of sensor data and control inputs to assess the risk and predict the goal of sensor spoofing attacks, determine which sensors are compromised, and recover the system.","PeriodicalId":199062,"journal":{"name":"2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131338416","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}