Biblio

Lightweight cryptography has been widely utilized in resource constrained embedded devices of Cyber-Physical System (CPS) terminals. The hostile and unattended environment in many scenarios make those endpoints easy to be attacked by hardware based techniques. As a resource-efficient countermeasure against Fault Attacks, parity Concurrent Error Detection (CED) is preferably integrated with security-critical algorithm in CPS terminals. The parity bit changes if an odd number of faults occur during the cipher execution. In this paper, we analyze the effectiveness of fault detection of a parity CED protected cipher (PRESENT) using laser fault injection. The experimental results show that the laser perturbation to encryption can easily flip an even number of data bits, where the faults cannot be detected by parity. Due to the similarity of different parity structures, our attack can bypass almost all parity protections in block ciphers. Some suggestions are given to enhance the security of parity implementations.

An approach to analyzing the security of a cyber-physical system (CPS) is proposed, where the behavior of a physical plant and its controller are captured in approximate models, and their interaction is rigorously checked to discover potential attacks that involve a varying number of compromised sensors and actuators. As a preliminary study, this approach has been applied to a fully functional water treatment testbed constructed at the Singapore University of Technology and Design. The analysis revealed previously unknown attacks that were confirmed to pose serious threats to the safety of the testbed, and suggests a number of research challenges and opportunities for applying a similar type of formal analysis to cyber-physical security.

Wireless sensor-actuator networks (WSANs) are being adopted in process industries because of their advantages in lowering deployment and maintenance costs. While there has been significant theoretical advancement in networked control design, only limited empirical results that combine control design with realistic WSAN standards exist. This paper presents a cyber-physical case study on a wireless process control system that integrates state-of-the-art network control design and a WSAN based on the WirelessHART standard. The case study systematically explores the interactions between wireless routing and control design in the process control plant. The network supports alternative routing strategies, including single-path source routing and multi-path graph routing. To mitigate the effect of data loss in the WSAN, the control design integrates an observer based on an Extended Kalman Filter with a model predictive controller and an actuator buffer of recent control inputs. We observe that sensing and actuation can have different levels of resilience to packet loss under this network control design. We then propose a flexible routing approach where the routing strategy for sensing and actuation can be configured separately. Finally, we show that an asymmetric routing configuration with different routing strategies for sensing and actuation can effectively improve control performance under significant packet loss. Our results highlight the importance of co-joining the design of wireless network protocols and control in wireless control systems.

Our position is that a key component of securing cyber-physical systems (CPS) is to develop a theory of accountability that encompasses both control and computing systems. We envision that a unified theory of accountability in CPS can be built on a foundation of causal information flow analysis. This theory will support design and analysis of mechanisms at various stages of the accountability regime: attack detection, responsibility-assignment (e.g., attack identification or localization), and corrective measures (e.g., via resilient control) As an initial step in this direction, we summarize our results on attack detection in control systems. We use the Kullback-Liebler (KL) divergence as a causal information flow measure. We then recover, using information flow analyses, a set of existing results in the literature that were previously proved using different techniques. These results cover passive detection, stealthy attack characterization, and active detection. This research direction is related to recent work on accountability in computational systems [1], [2], [3], [4]. We envision that by casting accountability theories in computing and control systems in terms of causal information flow, we can provide a common foundation to develop a theory for CPS that compose elements from both domains.

Notions like security, trust, and privacy are crucial in the digital environment and in the future, with the advent of technologies like the Internet of Things (IoT) and Cyber-Physical Systems (CPS), their importance is only going to increase. Trust has different definitions, some situations rely on real-world relationships between entities while others depend on robust technologies to gain trust after deployment. In this paper we focus on these robust technologies, their evolution in past decades and their scope in the near future. The evolution of robust trust technologies has involved diverse approaches, as a consequence trust is defined, understood and ascertained differently across heterogeneous domains and technologies. In this paper we look at digital trust technologies from the point of view of security and examine how they are making secure computing an attainable reality. The paper also revisits and analyses the Trusted Platform Module (TPM), Secure Elements (SE), Hypervisors and Virtualisation, Intel TXT, Trusted Execution Environments (TEE) like GlobalPlatform TEE, Intel SGX, along with Host Card Emulation, and Encrypted Execution Environment (E3). In our analysis we focus on these technologies and their application to the emerging domains of the IoT and CPS.

The communication infrastructure is a key element for management and control of the power system in the smart grid. The communication infrastructure, which can include equipment using off-the-shelf vulnerable operating systems, has the potential to increase the attack surface of the power system. The interdependency between the communication and the power system renders the management of the overall security risk a challenging task. In this paper, we address this issue by presenting a mathematical model for identifying and hardening the most critical communication equipment used in the power system. Using non-cooperative game theory, we model interactions between an attacker and a defender. We derive the minimum defense resources required and the optimal strategy of the defender that minimizes the risk on the power system. Finally, we evaluate the correctness and the efficiency of our model via a case study.

Healing Process is a major role in developing resiliency in cyber-physical system where the environment is diverse in nature. Cyber-physical system is modelled with Multi Agent Paradigm and biological inspired Danger Theory based-Artificial Immune Recognization2 Algorithm Methodology towards developing healing process. The Proposed methodology is implemented in a simulation environment and percentage of Convergence rates shown in achieving accuracy in the healing process to resiliency in cyber-physical system environment is shown.

In this paper, we investigate the resilient cumulant game control problem for a cyber-physical system. The cyberphysical system is modeled as a linear hybrid stochastic system with full-state feedback. We are interested in 2-player cumulant Nash game for a linear Markovian system with quadratic cost function where the players optimize their system performance by shaping the distribution of their cost function through cost cumulants. The controllers are optimally resilient against control feedback gain variations.We formulate and solve the coupled first and second cumulant Hamilton-Jacobi-Bellman (HJB) equations for the dynamic game. In addition, we derive the optimal players strategy for the second cost cumulant function. The efficiency of our proposed method is demonstrated by solving a numerical example.

Smart grid is a cyber-physical system that integrates power infrastructures with information technologies. To facilitate efficient information exchange, wireless networks have been proposed to be widely used in the smart grid. However, the jamming attack that constantly broadcasts radio interference is a primary security threat to prevent the deployment of wireless networks in the smart grid. Hence, spread spectrum systems, which provide jamming resilience via multiple frequency and code channels, must be adapted to the smart grid for secure wireless communications, while at the same time providing latency guarantee for control messages. An open question is how to minimize message delay for timely smart grid communication under any potential jamming attack. To address this issue, we provide a paradigm shift from the case-by-case methodology, which is widely used in existing works to investigate well-adopted attack models, to the worst-case methodology, which offers delay performance guarantee for smart grid applications under any attack. We first define a generic jamming process that characterizes a wide range of existing attack models. Then, we show that in all strategies under the generic process, the worst-case message delay is a U-shaped function of network traffic load. This indicates that, interestingly, increasing a fair amount of traffic can in fact improve the worst-case delay performance. As a result, we demonstrate a lightweight yet promising system, transmitting adaptive camouflage traffic (TACT), to combat jamming attacks. TACT minimizes the message delay by generating extra traffic called camouflage to balance the network load at the optimum. Experiments show that TACT can decrease the probability that a message is not delivered on time in order of magnitude.

Infrastructural systems such as the electricity grid, healthcare, and transportation networks today rely increasingly on the joint functioning of networked information systems and physical components, in short, on cyber-physical architectures. Despite tremendous advances in cryptography, physical-layer security and authentication, information attacks, both passive such as eavesdropping, and active such as unauthorized data injection, continue to thwart the reliable functioning of networked systems. In systems with joint cyber-physical functionality, the ability of an adversary to monitor transmitted information or introduce false information can lead to sensitive user data being leaked or result in critical damages to the underlying physical system. This paper investigates two broad challenges in information security in cyber-physical systems (CPSs): preventing retrieval of internal physical system information through monitored external cyber flows, and limiting the modification of physical system functioning through compromised cyber flows. A rigorous analytical framework grounded on information-theoretic security is developed to study these challenges in a general stochastic control system abstraction-a theoretical building block for CPSs-with the objectives of quantifying the fundamental tradeoffs between information security and physical system performance, and through the process, designing provably secure controller policies. Recent results are presented that establish the theoretical basis for the framework, in addition to practical applications in timing analysis of anonymous systems, and demand response systems in a smart electricity grid.

Cyber-physical systems (CPSs), due to their direct influence on the physical world, have to meet extended security and dependability requirements. This is particularly true for CPS that operate in close proximity to humans or that control resources that, when tampered with, put all our lives at stake. In this paper, we review the challenges and some early solutions that arise at the architectural and operating-system level when we require cyber-physical systems and CPS infrastructure to withstand advanced and persistent threats. We found that although some of the challenges we identified are already matched by rudimentary solutions, further research is required to ensure sustainable and dependable operation of physically exposed CPS infrastructure and, more importantly, to guarantee graceful degradation in case of malfunction or attack.

Feedback loss can severely degrade the overall system performance, in addition, it can affect the control and computation of the Cyber-physical Systems (CPS). CPS hold enormous potential for a wide range of emerging applications including stochastic and time-critical traffic patterns. Stochastic data has a randomness in its nature which make a great challenge to maintain the real-time control whenever the data is lost. In this paper, we propose a data recovery scheme, called the Efficient Temporal and Spatial Data Recovery (ETSDR) scheme for stochastic incomplete feedback of CPS. In this scheme, we identify the temporal model based on the traffic patterns and consider the spatial effect of the nearest neighbor. Numerical results reveal that the proposed ETSDR outperforms both the weighted prediction (WP) and the exponentially weighted moving average (EWMA) algorithm regardless of the increment percentage of missing data in terms of the root mean square error, the mean absolute error, and the integral of absolute error.
 

The unified power flow controller (UPFC) has attracted much attention recently because of its capability in controlling the active and reactive power flows. The normal operation of UPFC is dependent on both its physical part and the associated cyber system. Thus malicious cyber attacks may impact the reliability of UPFC. As more information and communication technologies are being integrated into the current power grid, more frequent occurrences of cyber attacks are possible. In this paper, the cyber architecture of UPFC is analyzed, and the possible attack scenarios are considered and discussed. Based on the interdependency of the physical part and the cyber part, an integrated reliability model for UPFC is proposed and analyzed. The impact of UPFC on the overall system reliability is examined, and it is shown that cyber attacks against UPFC may yield an adverse influence.

A Cyber-Physical System (CPS) integrates physical devices (i.e., sensors) with cyber (i.e., informational) components to form a context sensitive system that responds intelligently to dynamic changes in real-world situations. Such a system has wide applications in the scenarios of traffic control, battlefield surveillance, environmental monitoring, and so on. A core element of CPS is the collection and assessment of information from noisy, dynamic, and uncertain physical environments integrated with many types of cyber-space resources. The potential of this integration is unbounded. To achieve this potential the raw data acquired from the physical world must be transformed into useable knowledge in real-time. Therefore, CPS brings a new dimension to knowledge discovery because of the emerging synergism of the physical and the cyber. The various properties of the physical world must be addressed in information management and knowledge discovery. This paper discusses the problems of mining sensor data in CPS: With a large number of wireless sensors deployed in a designated area, the task is real time detection of intruders that enter the area based on noisy sensor data. The framework of IntruMine is introduced to discover intruders from untrustworthy sensor data. IntruMine first analyzes the trustworthiness of sensor data, then detects the intruders' locations, and verifies the detections based on a graph model of the relationships between sensors and intruders.

Cyber-Physical System(CPS) is now a new evolutional morphology of embedded systems. With features of merging computation and physical processes together, the traditional verification and simulation methods have being challenged recently. After analyzed the state-of-art of related research, a new simulation environment is studied according to the characters of a special autonomous cyber-physical system-Unmanned Aerial Vehicle, and designed to be scene-driven, modeling and reconfigurable. In this environment, a novel CPS-in-loop architecture, which can support simulations under different customized scenes, is studied firstly to ensure its opening and flexibility. And as another foundation, some dynamics models of CPS and atmospheric ones of relative sensors are introduced to simulate the motion of CPS and the change of its posture. On the basis above, the reconfigurable scene-driven mechanisms that are Based on hybrid events are mainly excogitated. Then, different scenes can be configured in terms of special verification requirements, and then each scene will be decomposed into a spatio-temporal event sequence and scheduled by a scene executor. With this environment, not only the posture of CPS, but also the autonomy of its behavior can be verified and observed. It will be meaningful for the design of such autonomous CPS.