Visible to the public International Conferences: ICCPS 2015, Seattle, WA

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International Conferences:

ICCPS 2015 

Seattle, WA

The 6th International Conference on Cyber-Physical Systems (ICCPS) was held in Seattle, Washington on April 14–16, 2015. The conference presentations covered a variety of issues and topics in cyber-physical systems. The ones cited here focus on the hard problems of cyber-physical system security, privacy, and human behavior and interaction.  

Tamara Bonaci, Junjie Yan, Jeffrey Herron, Tadayoshi Kohno, Howard Jay Chizeck; “Experimental Analysis of Denial-of-Service Attacks on Teleoperated Robotic Systems,” in ICCPS ’15, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, April 2015, Pages 11–20. doi:10.1145/2735960.2735980
Abstract: Applications of robotic systems have had an explosive growth in recent years. In 2008, more than eight million robots were deployed worldwide in factories, battlefields, and medical services. The number and the applications of robotic systems are expected to continue growing, and many future robots will be controlled by distant operators through wired and wireless communication networks.  The open and uncontrollable nature of communication media between robots and operators renders these cyber-physical systems vulnerable to a variety of cyber-security threats, many of which cannot be prevented using traditional cryptographic methods. A question thus arises: what if teleoperated robots are attacked, compromised or taken over?  In this paper, we systematically analyze cyber-security attacks against Raven II R, an advanced teleoperated robotic surgery system. We classify possible threats, and focus on denial-of-service (DoS) attacks, which cannot be prevented using available cryptographic solutions. Through a series of experiments involving human subjects, we analyze the impact of these attacks on teleoperated procedures. We use the Fitts’ law as a way of quantifying the impact, and measure the increase in tasks’ difficulty when under DoS attacks.  We then consider possible steps to mitigate the identified DoS attacks, and evaluate the applicability of these solutions for teleoperated robotics. The broader goal of our paper is to raise awareness, and increase understanding of emerging cyber-security threats against teleoperated robotic systems.
Keywords: Fitts’ law, cyber-physical systems, cybersecurity threats, denial-of-service attacks, teleoperated robotic systems (ID#: 15-6841)


Alexandre Bayen, Michael Branicky; “Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems,” ICCPS ’15, the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, Seattle, WA, April 14–16, 2015. ACM 2015. ISBN: 978-1-4503-3455-6.
Abstract: This volume contains the papers presented at the Sixth ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS 2015), which was held with the Cyber-Physical Systems Week in Seattle, Washington, USA, on 13--16 April 2015. ICCPS has been the flagship conference on Cyber-Physical Systems (CPS) that tightly couple the cyber aspects of computing and communications with the physical aspects of dynamics and engineering. ICCPS, as an integral part of CPS Week, is pleased to be co-located with its sister conferences that focus on various components of CPS including embedded systems, hybrid systems, real-time systems, and wireless sensor networks.  ICCPS aims to showcase cutting-edge research that spans both the cyber and physical aspects of CPS. In the process, it will bring together engineers from various disciplines and computer scientists to create the scientific foundations, identify new principles, present novel architectures, demonstrate promising applications, and enable powerful capabilities of CPS. In addition to its traditional focus on the foundations, applications, and examples of CPS, this year ICCPS has absorbed the former High Confidence Networked Systems (HiCoNS) conference and includes its focus on secure and resilient infrastructure for CPS.
Keywords: (not provided) (ID#: 15-6842)


Abdulmalik Humayed, Bo Luo; “Cyber-Physical Security for Smart Cars: Taxonomy of Vulnerabilities, Threats, and Attacks,” ICCPS ’15, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, April 2015, Pages 252–253. doi:10.1145/2735960.2735992
Abstract: As the passenger vehicles evolve to be “smart”, electronic components, including communication and intelligent software, are continuously introduced to new models and concept vehicles. The new paradigm introduces new features and benefits, but also brings new security concerns.  Smart cars are considered cyber-physical systems (CPS) because of their integration of cyber- and physical-components. In recent years, various threats, vulnerabilities, and attacks have been discovered from different models of smart cars. In the worst-case scenario, external attackers may remotely obtain full control of the vehicle by exploiting an existing vulnerability. In this poster, we examine smart car security from a CPS’ perspective, and derive a taxonomy of threats, vulnerabilities, and attacks. We demonstrate a systematic model of smart car security by distinguishing between cyber, cyber-physical, and physical (C-CP-P) components and their interactions. We present our reflections on how the systematic model and taxonomy could be utilized to help the development of effective control mechanisms.
Keywords: (not provided) (ID#: 15-6843)


Junkil Park, Radoslav Ivanov, James Weimer, Miroslav Pajic, Insup Lee; “Sensor Attack Detection in the Presence of Transient Faults,” ICCPS ’15, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, April 2015, 
Pages 1–10. doi:10.1145/2735960.2735984
Abstract: This paper addresses the problem of detection and identification of sensor attacks in the presence of transient faults. We consider a system with multiple sensors measuring the same physical variable, where some sensors might be under attack and provide malicious values. We consider a setup, in which each sensor provides the controller with an interval of possible values for the true value. While approaches exist for detecting malicious sensor attacks, they are conservative in that they treat attacks and faults in the same way, thus neglecting the fact that sensors may provide faulty measurements at times due to temporary disturbances (e.g., a tunnel for GPS). To address this problem, we propose a transient fault model for each sensor and an algorithm designed to detect and identify attacks in the presence of transient faults. The fault model consists of three aspects: the size of the sensor’s interval (1) and an upper bound on the number of errors (2) allowed in a given window size (3). Given such a model for each sensor, the algorithm uses pairwise inconsistencies between sensors to detect and identify attacks. In addition to the algorithm, we provide a framework for selecting a fault model for each sensor based on training data. Finally, we validate the algorithm’s performance on real measurement data obtained from an unmanned ground vehicle.
Keywords: (not provided) (ID#: 15-6844)


Jackeline Abad Torres, Dinuka Sahabandu, Rahul Dhal, Sandip Roy; “Local Open- and Closed-Loop Manipulation of Multi-Agent Networks,” ICCPS ’15, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, April 2015, Pages 21–30. doi:10.1145/2735960.2735982
Abstract: We explore the manipulation of networked cyber-physical devices via external actuation or feedback control at a single location, in the context of a canonical multi-agent system model known as the double integrator network. One main focus is to understand whether or not, and how easily, a stakeholder can manipulate network’'s full dynamics by designing the actuation signal for one agent (in an open-loop sense). Additionally, we investigate the ability of the stakeholder to manipulate the multi-agent system, and achieve control objectives, via local feedback control. For both problems, we find that manipulation of the dynamics is crucially dependent on the network’s graph and associated spectrum.
Keywords: controllability, cyber-physical systems, multi-agent systems (ID#: 15-6845)


Jian Xu, Vasiliki Sfyrla, Krishna K. Venkatasubramanian; “Methodology for Generating Attack Trees for Interoperable Medical Devices,” ICCPS ’15, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, April 2015,
Pages  258–258. doi:10.1145/2735960.2735993
Abstract: In this paper we present a methodology that provides a systematic way of generating attack trees for interoperable medical devices by leveraging process modeling, hazard descriptions, and fault-trees.
Keywords: (not provided) (ID#: 15-6846)


Taylor T. Johnson, Stanley Bak, Steven Drager; “Cyber-Physical Specification Mismatch Identification with Dynamic Analysis,” ICCPS ’15, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, April 2015, Pages 208–217. doi:10.1145/2735960.2735979
Abstract: Embedded systems use increasingly complex software and are evolving into cyber-physical systems (CPS) with sophisticated interaction and coupling between physical and computational processes. Many CPS operate in safety-critical environments and have stringent certification, reliability, and correctness requirements. These systems undergo changes throughout their lifetimes, where either the software or physical hardware is updated in subsequent design iterations. One source of failure in safety-critical CPS is when there are unstated assumptions in either the physical or cyber parts of the system, and new components do not match those assumptions. In this work, we present an automated method towards identifying unstated assumptions in CPS. Dynamic specifications in the form of candidate invariants of both the software and physical components are identified using dynamic analysis (executing and/or simulating the system implementation or model thereof). A prototype tool called Hynger (for HYbrid iNvariant GEneratoR) was developed that instruments Simulink/Stateflow (SLSF) model diagrams to generate traces in the input format compatible with the Daikon invariant inference tool, which has been extensively applied to software systems. Hynger, in conjunction with Daikon, is able to detect candidate invariants of several CPS case studies. We use the running example of a DC-to-DC power converter, and demonstrate that Hynger can detect a specification mismatch where a tolerance assumed by the software is violated due to a plant change.
Keywords: cyber-physical systems, dynamic analysis, specifications (ID#: 15-6847)


Xiaodong Zhang, Matthew Clark, Kudip Rattan, Jonathan Muse; “Controller Verification in Adaptive Learning Systems Towards Trusted Autonomy,” ICCPS ’15, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, April 2015, Pages 31–40.  doi:10.1145/2735960.2735971
Abstract: With the increasing levels of adaptation and autonomy in complex cyber-physical systems (CPS), the traditional notion that such systems can be fully tested and validated offline is becoming an impossible task. It is virtually impossible to analyze or test ahead of time all the possible parameter values resulting from the uncertainty in system operational and environmental conditions. This paper considers the problem of online controller verification in a class of first-order nonlinear uncertain systems incorporating neural network based learning algorithms. Based on several critical assumptions, an on-line neural network model is employed to ensure robustness and fault-tolerance to certain modeling uncertainty and physical faults under consideration. However, these assumptions may be violated in the presence of software faults or unanticipated physical faults in the closed-loop system, leading to unstable learning behaviors and controller malfunctions. Based on Lyapunov stability theory, an online controller verification scheme is developed to detect such unstable learning behaviors by continuously monitoring the decrease of Lyapunov functions. Adaptive thresholds for detecting malfunctions of the adaptive learning controller are derived, ensuring the robustness with respect to modeling uncertainty and neural network approximation error. Additionally, the detectability conditions are investigated, characterizing the class of detectable software faults and unanticipated hardware faults. An upper bound on the detection time of controller malfunction is also derived. Some simulation results using a two-tank system are shown to illustrate the effectiveness of the controller verification method.
Keywords: adaptive learning systems, fault detection, neural networks, verification and validation of control systems (ID#: 15-6848)


Yunlong Gao, Shaohan Hu, Renato Mancuso, Hongwei Wang, Minje Kim, PoLiang Wu, Lu Su, Lui Sha, Tarek Abdelzaher; “Exploiting Structured Human Interactions to Enhance Estimation Accuracy in Cyber-Physical Systems,” ICCPS ’15, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, April 2015, Pages 60–69. doi:10.1145/2735960.2735965
Abstract: In this paper, we describe a general methodology for enhancing measurement accuracy in cyber-physical systems that involve structured human interactions with a noisy physical environment. We define structured human interactions as those that follow a domain-specific workflow. The idea of the paper is simple: we exploit knowledge of the workflow to correct unreliable sensor data. The intellectual contribution lies in an algorithm for joint estimation of the current state of the workflow together with correction of noisy sensor measurements, given only the noisy measurements and an overall workflow description. We demonstrate through simulations and a physical implementation the degree to which knowledge of workflow can increase sensing accuracy. As a specific instantiation of this idea, we present a novel situation-awareness tool called the Emergency Transcriber designed to automatically document operational procedures followed by teams of first responders in emergency-response scenarios. Evaluation shows that our system provides a significant fidelity enhancement over the state of the art, effectively coping with the noisy environment of emergency teams.
Keywords: emergency, unreliable sensor data, workflow (ID#: 15-6849)


Kyong-Tak Cho, Kang G. Shin, Taejoon Park; “CPS Approach to Checking Norm Operation of a Brake-by-Wire System,” ICCPS ’15, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, April 2015, Pages 41–50. doi:10.1145/2735960.2735977
Abstract: For better controllability and energy-efficiency, more vehicle functions are being implemented via electronic control systems in place of traditional mechanical control systems. However, such transitions are creating new, unprecedented risks such as software bugs or hardware glitches, all of which can lead to serious safety risks. Recent real-world examples and research literature have been covering them under the name of vehicle misbehavior. In this paper, we present a new way of checking norm operations, called BAD (Brake Anomaly Detection), which detects any vehicle misbehavior in the Brake-by-Wire system. We focus on the braking system since it is a prototypical safety-critical and cyber-physical system. We first propose a new method for constructing norm models of braking and then show how anomalies are detected by BAD using the constructed models. Finally, we discuss how to verify the results, especially in the context of false positives. Our evaluation results show that BAD can effectively detect various types of anomaly in the braking system.
Keywords: anomaly detection, braking system, vehicle misbehavior (ID#: 15-6851)


Lu Feng, Clemens Wiltsche, Laura Humphrey, Ufuk Topcu; “Controller Synthesis for Autonomous Systems Interacting with Human Operators,” ICCPS ’15, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, April 2015, Pages 70–79. doi:10.1145/2735960.2735973
Abstract: We propose an approach to synthesize control protocols for autonomous systems that account for uncertainties and imperfections in interactions with human operators. As an illustrative example, we consider a scenario involving road network surveillance by an unmanned aerial vehicle (UAV) that is controlled remotely by a human operator but also has a certain degree of autonomy. Depending on the type (i.e., probabilistic and/or nondeterministic) of knowledge about the uncertainties and imperfections in the operator-autonomy interactions, we use abstractions based on Markov decision processes and augment these models to stochastic two-player games. Our approach enables the synthesis of operator-dependent optimal mission plans for the UAV, highlighting the effects of operator characteristics (e.g., workload, proficiency, and fatigue) on UAV mission performance; it can also provide informative feedback (e.g., Pareto curves showing the trade-offs between multiple mission objectives), potentially assisting the operator in decision-making.
Keywords: (not provided) (ID#: 15-6852)


Nisar Ahmed, Mark Campbell, David Casbeer, Yongcan Cao, Derek Kingston; “Fully Bayesian Learning and Spatial Reasoning with Flexible Human Sensor Networks,” ICCPS ’15, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, April 2015, Pages 80–89. doi:10.1145/2735960.2735970
Abstract: This work considers the challenging problem of simultaneous modeling and fusion of ‘soft data’ generated by a network of ‘human sensors’ for spatial state estimation tasks, such as lost target search or large area surveillance. Human sensors can opportunistically provide useful information to constrain difficult state estimation problems, but are imperfect information sources whose reliability cannot be easily determined in advance. Formal observation likelihood models are derived for flexible sketch-based observations, but are found to lead to analytically intractable statistical dependencies between unknown sensor parameters and spatial states of interest that cannot adequately characterized by simple point estimates. Hierarchical Bayesian models and centralized inference strategies based on Gibbs sampling are proposed to address these issues, especially in cases of sparse, noisy, ambiguous and conflicting soft data. This leads to an automatic online calibration procedure for human sensor networks, as well as conservative spatial state posteriors that naturally account for model uncertainties. Experimental outdoor target search results with real spatial human sensor data (obtained via networked mobile graphical sketch interfaces) demonstrate the proposed methodology.
Keywords: autonomous sensor networks, human-in-the-loop, statistical signal processing (ID#: 15-6853)


Ming Jin, Lillian J. Ratliff, Ioannis Konstantakopoulos, Costas Spanos, Shankar Sastry; “REST: A Reliable Estimation of Stopping Time Algorithm for Social Game Experiments,” ICCPS ’15, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, April 2015, Pages 90–99. doi:10.1145/2735960.2735974
Abstract: Through a social game, we integrate building occupants into the control and management of an office building that is instrumented with networked embedded systems for sensing and actuation. The goal of the social game is to both incentivize building occupants to be more energy efficient and learn behavioral models for occupants so that the building can be made sustainable through automation. Given a generative model for the occupants behavior in the competitive environment created by the social game, we develop a method for learning the parameters of the behavioral model as we conduct the experiment by adopting a learning to learn framework. Using tools from statistical learning, we provide bounds on the parameter inference error. In addition, we provide an algorithm for computing the stopping time required for a specified level of confidence in estimation. We show the performance of our algorithm in several examples.
Keywords: (not provided) (ID#: 15-6854)


Huihua Zhao, Jake Reher, Jonathan Horn, Victor Paredes, Aaron D. Ames; “Realization of Nonlinear Real-Time Optimization Based Controllers on Self-Contained Transfemoral Prosthesis,” ICCPS ’15, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, April 2015, Pages 130–138. doi:10.1145/2735960.2735964
Abstract: Lower-limb prosthesis provide a prime example of cyber-physical systems (CPSs) that interact with humans in a safety critical fashion, and therefore require the synergistic development of sensing, algorithms and controllers. With a view towards better understanding CPSs of this form, this paper presents a methodology for successfully translating nonlinear real-time optimization based controllers from bipedal robots to a novel custom built self-contained powered transfemoral prosthesis: AMPRO. To achieve this goal, we begin by collecting reference human locomotion data via Inertial measurement Units (IMUs). This data forms the basis for an optimization problem that generates virtual constraints, i.e., parametrized trajectories, for the prosthesis that provably yields walking in simulation. Leveraging methods that have proven successful in generating stable robotic locomotion, control Lyapunov function (CLF) based Quadratic Programs (QPs) are utilized to optimally track the resulting desired trajectories. The parameterization of the trajectories is determined through a combination of on-board sensing on the prosthesis together with IMU data, thereby coupling the actions of the user with the controller. Finally, impedance control is integrated into the QP yielding an optimization based control law that displays remarkable tracking and robustness, outperforming traditional PD and impedance control strategies. This is demonstrated experimentally on AMPRO through the implementation of the holistic sensing, algorithm and control framework, with the end result being stable and human-like walking.
Keywords: hybrid systems, nonlinear control, transfemoral prosthesis (ID#: 15-6855)


Kun Zhang, Jonathan Sprinkle, Ricardo G. Sanfelice; “A Hybrid Model Predictive Controller for Path Planning and Path Following,” ICCPS ’15, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, April 2015, Pages 139–148. doi:10.1145/2735960.2735966
Abstract: The use of nonlinear model-predictive methods for path planning and following has the advantage of concurrently solving problems of obstacle avoidance, feasible trajectory selection, and trajectory following, while obeying constraints on control inputs and state values. However, such approaches are computationally intensive, and may not be guaranteed to return a result in bounded time when performing a non-convex optimization. This problem is an interesting application to cyber-physical systems due to their reliance on computation to carry out complex control. The computational burden can be addressed through model reduction, at a cost of potential (bounded) model error over the prediction horizon. In this paper we introduce a metric called uncontrollable divergence, and discuss how the selection of the model to use for the predictive controller can be addressed by evaluating this metric, which reveals the divergence between predicted and true states caused by return time and model mismatch. A map of uncontrollable divergence plotted over the state space gives the criterion to judge where reduced models can be tolerated when high update rate is preferred (e.g. at high speed and small steering angles), and where high-fidelity models are required to avoid obstacles or make tighter curves (e.g. at large steering angles). With this metric, we design a hybrid controller that switches at runtime between predictive controllers in which respective models are deployed.
Keywords: MPC, hybrid control, model error evaluation (ID#: 15-6856)


Zhishan Guo, Sanjoy K. Baruah; “Uniprocessor EDF Scheduling of AVR Task Systems,” ICCPS ’15, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, April 2015, Pages 159–168. doi:10.1145/2735960.2735976
Abstract: The adaptive varying-rate (AVR) task model has been proposed as a means of modeling certain physically-derived constraints in CPS’s in a manner that is more accurate (less pessimistic) than is possible using prior task models from real-time scheduling theory. Existing work on schedulability analysis of systems of AVR tasks is primarily restricted to fixed-priority scheduling; this paper establishes schedulability analysis results for systems of AVR and sporadic tasks under Earliest Deadline First (EDF) scheduling. The proposed analysis techniques are evaluated both theoretically via the speedup factor metric, and experimentally via schedulability experiments on randomly-generated task systems.
Keywords: (not provided) (ID#: 15-6857)


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