Biblio

This paper is concered with the nonlinear cyber physical system (CPS) with uncertain parameters under false data injection (FDI) attacks. The interval type-2 (IT2) fuzzy model is utilized to approximate the nonlinear system, then the nonlinear system can be represented as a convex combination of linear systems. To detect the FDI attacks, a novel robust fuzzy extended state observer with H∞ preformance is proposed, where the fuzzy rules are utilized to the observer to estimate the FDI attacks. Utilizing the observation of the FDI attacks, a security control scheme is proposed in this paper, in which a compensator is designed to offset the FDI attacks. Simulation examples are given to illustrate the effecitveness of the proposed security scheme.

Actuator malfunctions may have disastrous con-sequences for systems not designed to mitigate them. We focus on the loss of control authority over actuators, where some actuators are uncontrolled but remain fully capable. To counter-act the undesirable outputs of these malfunctioning actuators, we use real-time measurements and redundant actuators. In this setting, a system that can still reach its target is deemed resilient. To quantify the resilience of a system, we compare the shortest time for the undamaged system to reach the target with the worst-case shortest time for the malfunctioning system to reach the same target, i.e., when the malfunction makes that time the longest. Contrary to prior work on driftless linear systems, the absence of analytical expression for time-optimal controls of general linear systems prevents an exact calculation of quantitative resilience. Instead, relying on Lyapunov theory we derive analytical bounds on the nominal and malfunctioning reach times in order to bound quantitative resilience. We illustrate our work on a temperature control system.

In this paper, we investigate the conditions for the existence of dynamically undetectable attacks and perfectly undetectable attacks. Then we provide a quantitative measure on the security for discrete-time linear time-invariant (LTI) systems under both actuator and sensor attacks based on undetectability. Finally, the computation of proposed security index is reduced to a min-cut problem for the structured systems by graph theory. Numerical examples are provided to illustrate the theoretical results.

Attack detection and recovery are fundamental elements for the operation of safe and resilient cyber-physical systems. Most of the literature focuses on attack-detection, while leaving attack-recovery as an open problem. In this paper, we propose novel attack-recovery control for securing cyber-physical systems. Our recovery control consists of new concepts required for a safe response to attacks, which includes the removal of poisoned data, the estimation of the current state, a prediction of the reachable states, and the online design of a new controller to recover the system. The synthesis of such recovery controllers for cyber-physical systems has barely investigated so far. To fill this void, we present a formal method-based approach to online compute a recovery control sequence that steers a system under an ongoing sensor attack from the current state to a target state such that no unsafe state is reachable on the way. The method solves a reach-avoid problem on a Linear Time-Invariant (LTI) model with the consideration of an error bound $ε$ $\geq$ 0. The obtained recovery control is guaranteed to work on the original system if the behavioral difference between the LTI model and the system's plant dynamics is not larger than $ε$. Since a recovery control should be obtained and applied at the runtime of the system, in order to keep its computational time cost as low as possible, our approach firstly builds a linear programming restriction with the accordingly constrained safety and target specifications for the given reach-avoid problem, and then uses a linear programming solver to find a solution. To demonstrate the effectiveness of our method, we provide (a) the comparison to the previous work over 5 system models under 3 sensor attack scenarios: modification, delay, and reply; (b) a scalability analysis based on a scalable model to evaluate the performance of our method on large-scale systems.

As large-scale linear equation systems are pervasive in many scientific fields, great efforts have been done over the last decade in realizing efficient techniques to solve such systems, possibly relying on High Performance Computing (HPC) infrastructures to boost the performance. In this framework, the ever-growing scale of supercomputers inevitably increases the frequency of faults, making it a crucial issue of HPC application development.A previous study [1] investigated the possibility to enhance the Inhibition Method (IMe) -a linear systems solver for dense unstructured matrices-with fault tolerance to single hard errors, i.e. failures causing one computing processor to stop.This article extends [1] by proposing an efficient technique to obtain fault tolerance to multiple hard errors, which may occur concurrently on different processors belonging to the same or different machines. An improved parallel implementation is also proposed, which is particularly suitable for HPC environments and moves towards the direction of a complete decentralization. The theoretical analysis suggests that the technique (which does not require check pointing, nor rollback) is able to provide fault tolerance to multiple faults at the price of a small overhead and a limited number of additional processors to store the checksums. Experimental results on a HPC architecture validate the theoretical study, showing promising performance improvements w.r.t. a popular fault-tolerant solving technique.

This paper studies initial-value privacy problems of linear dynamical systems. We consider a standard linear time-invariant system with random process and measurement noises. For such a system, eavesdroppers having access to system output trajectories may infer the system initial states, leading to initial-value privacy risks. When a finite number of output trajectories are eavesdropped, we consider a requirement that any guess about the initial values can be plausibly denied. When an infinite number of output trajectories are eavesdropped, we consider a requirement that the initial values should not be uniquely recoverable. In view of these two privacy requirements, we define differential initial-value privacy and intrinsic initial-value privacy, respectively, for the system as metrics of privacy risks. First of all, we prove that the intrinsic initial-value privacy is equivalent to unobservability, while the differential initial-value privacy can be achieved for a privacy budget depending on an extended observability matrix of the system and the covariance of the noises. Next, the inherent network nature of the considered linear system is explored, where each individual state corresponds to a node and the state and output matrices induce interaction and sensing graphs, leading to a network system. Under this network system perspective, we allow the initial states at some nodes to be public, and investigate the resulting intrinsic initial- value privacy of each individual node. We establish necessary and sufficient conditions for such individual node initial-value privacy, and also prove that the intrinsic initial-value privacy of individual nodes is generically determined by the network structure.

Given a network with a set of vulnerable actuators (and sensors), the security index of an actuator equals the minimum number of sensors and actuators that needs to be compromised so as to conduct a perfectly undetectable attack using the said actuator. This paper deals with the problem of computing actuator security indices for discrete-time LTI network systems, using a structured systems framework. We show that the actuator security index is generic, that is for almost all realizations the actuator security index remains the same. We refer to such an index as generic security index (generic index) of an actuator. Given that the security index quantifies the vulnerability of a network, the generic index is quite valuable for large scale energy systems. Our second contribution is to provide graph-theoretic conditions for computing the generic index. The said conditions are in terms of existence of linkings on appropriately-defined directed (sub)graphs. Based on these conditions, we present an algorithm for computing the generic index.

The security of Cyber-physical systems has been a hot topic in recent years. There are two main focuses in this area: Firstly, what kind of attacks can avoid detection, i.e., the stealthiness of attacks. Secondly, what kind of systems can stay stable under stealthy attacks, i.e., the invulnerability of systems. In this paper, we will give a detailed characterization for stealthy attacks and detection criterion for such attacks. We will also study conditions for the vulnerability of a stochastic linear system under stealthy attacks.

We address the problem of distributed state estimation of a linear dynamical process in an attack-prone environment. A network of sensors, some of which can be compromised by adversaries, aim to estimate the state of the process. In this context, we investigate the impact of making a small subset of the nodes immune to attacks, or “trusted”. Given a set of trusted nodes, we identify separate necessary and sufficient conditions for resilient distributed state estimation. We use such conditions to illustrate how even a small trusted set can achieve a desired degree of robustness (where the robustness metric is specific to the problem under consideration) that could otherwise only be achieved via additional measurement and communication-link augmentation. We then establish that, unfortunately, the problem of selecting trusted nodes is NP-hard. Finally, we develop an attack-resilient, provably-correct distributed state estimation algorithm that appropriately leverages the presence of the trusted nodes.

In this paper, we propose a compositional scheme for the construction of abstractions for networks of control systems by using the interconnection matrix and joint dissipativity-type properties of subsystems and their abstractions. In the proposed framework, the abstraction, itself a control system (possibly with a lower dimension), can be used as a substitution of the original system in the controller design process. Moreover, we provide a procedure for constructing abstractions of a class of nonlinear control systems by using the bounds on the slope of system nonlinearities. We illustrate the proposed results on a network of linear control systems by constructing its abstraction in a compositional way without requiring any condition on the number or gains of the subsystems. We use the abstraction as a substitute to synthesize a controller enforcing a certain linear temporal logic specification. This example particularly elucidates the effectiveness of dissipativity-type compositional reasoning for large-scale systems.

We consider a compositional construction of approximate abstractions of interconnected control systems. In our framework, an abstraction acts as a substitute in the controller design process and is itself a continuous control system. The abstraction is related to the concrete control system via a so-called simulation function: a Lyapunov-like function, which is used to establish a quantitative bound between the behavior of the approximate abstraction and the concrete system. In the first part of the paper, we provide a small gain type condition that facilitates the compositional construction of an abstraction of an interconnected control system together with a simulation function from the abstractions and simulation functions of the individual subsystems. In the second part of the paper, we restrict our attention to linear control system and characterize simulation functions in terms of controlled invariant, externally stabilizable subspaces. Based on those characterizations, we propose a particular scheme to construct abstractions for linear control systems. We illustrate the compositional construction of an abstraction on an interconnected system consisting of four linear subsystems. We use the abstraction as a substitute to synthesize a controller to enforce a certain linear temporal logic specification.

With rapid development of deep integration of computation, control, and communication, Cyber-Physical Systems (CPSs) play an important role in industrial processes. Combined with the technology of fog computing, CPSs can outsource their complicated computation to the fog layer, which in turn, may bring security threats with regard to data privacy. To protect data privacy in a control framework, this paper investigate observer-based secure control problem towards fog computing aided CPSs (FCA-CPSs) by utilizing data perturbation method. Firstly, security inputs are designed to encrypt the transmitted states to realize specific confidentiality level. Then, sufficient conditions are established to ensure the stability of considered FCA-CPSs. Finally, a numerical example is provided to illustrate the effectiveness of the secure estimation scheme.

This paper is concerned with the stabilization problem of cyber physical system (CPS) exposed to a random replay attack. The study will ignore the effects of communication delays and packet losses, and the attention will be focused on the effect of replay attack on the stability of (CPS). The closed-loop system is modeled as Markovian jump linear system with two jumping parameters. Linear matrix inequality (LMI) formulation is used to give a condition for stochastic stabilization of the system. Finally the theory is illustrated through a numerical example.

Voice-based input is usually used as the primary input method for augmented reality (AR) headsets due to immersive AR experience and good recognition performance. However, recent researches have shown that an attacker can inject inaudible voice commands to the devices that lack voice verification. Even if we secure voice input with voice verification techniques, an attacker can easily steal the victim's voice using low-cast handy recorders and replay it to voice-based applications. To defend against voice-spoofing attacks, AR headsets should be able to determine whether the voice is from the person who is using the AR headsets. Existing voice-spoofing defense systems are designed for smartphone platforms. Due to the special locations of microphones and loudspeakers on AR headsets, existing solutions are hard to be implemented on AR headsets. To address this challenge, in this paper, we propose a voice-spoofing defense system for AR headsets by leveraging both the internal body propagation and the air propagation of human voices. Experimental results show that our system can successfully accept normal users with average accuracy of 97% and defend against two types of attacks with average accuracy of at least 98%.

Networked Control Systems (NCS) are widely used in Industry 4.0 to obtain better management and operational capabilities, as well as to reduce costs. However, despite the benefits provided by NCSs, the integration of communication networks with physical plants can also expose these systems to cyber threats. This work proposes a link monitoring strategy to identify linear time-invariant transfer functions performed by a Man-in-the-Middle during controlled data injection attacks in NCSs. The results demonstrate that the proposed identification scheme provides adequate accuracy when estimating the attack function, and does not interfere in the plant behavior when the system is not under attack.

Mitigating the effect of Distributed Denial of Service (DDoS) attacks in wired/wireless networks is a problem of extreme importance. The present paper investigates this problem and proposes a secure AQM to encounter the effects of DDoS attacks on queue's router. The employed method relies on modelling the TCP/AQM system subjected to different DoS attack rate where the resulting closed-loop system is expressed as new Markovian Jump Linear System (MJLS). Sufficient delay-dependent conditions which guarantee the syntheses of a stabilizing control for the closed-loop system with a guaranteed cost J* are derived. Finally, a numerical example is displayed.

As technology is developing exponentially and the world is moving towards automation, the resources have to be transferred through the internet which requires routers to connect networks and forward bundles (information). Due to the vulnerability of routers the data and resources have been hacked. The vulnerability of routers is due to minimum authentication to the network shared, some technical attacks on routers, leaking of passwords to others, single passwords. Based on the study, the solution is to maximize authentication of the router by embedding an application that monitors the user entry based on MAC address of the device, the password is frequently changed and that encrypted password is sent to a user and notifies the admin about the changes. Thus, these routers provide high-level security to the forward data through the internet.

In this article, we introduce a new method for computing fixed points of a class of iterated functions in a finite time, by exponentiating linear multivalued operators. To better illustrate this approach and show that our method can give fast and accurate results, we have chosen two well-known applications which are difficult to handle by usual techniques. First, we apply the exponentiation of linear operators to a digital filter in order to get a fine approximation of its behavior at an arbitrary time. Second, we consider a PID controller. To get a reliable estimate of its control function, we apply the exponentiation of a bundle of linear operators. Note that, our technique can be applied in a more general setting, i.e. for any multivalued linear map and that the general method is also introduced in this article.

In this paper, we address the stability problem of a noiseless linear time invariant control system over parallel Gaussian channels with feedback. It is shown that the eigenvalues-rate condition which has been proved as a necessary condition, is also sufficient for stability over parallel Gaussian channels. In fact, it is proved that for stabilizing a control system over the parallel Gaussian channels, it suffices that the Shannon channel capacity obtained by the water filling technique is greater than the sum of the logarithm of the unstable eigenvalues magnitude. In order to prove this sufficient condition, we propose a new nonlinear joint source channel coding for parallel Gaussian channels by which the initial state is transmitted through communication steps. This coding scheme with a linear control policy results in the stability of the system under the eigenvalues-rate condition. Hence, the proposed encoder, decoder and controller are efficient for this problem.

Resilient control systems should efficiently restore control into physical systems not only after the sabotage of themselves, but also after breaking physical systems. To enhance resilience of control systems, given an originally minimal-input controlled linear-time invariant(LTI) physical system, we address the problem of efficient control recovery into it after removing a known system vertex by finding the minimum number of inputs. According to the minimum input theorem, given a digraph embedded into LTI model and involving a precomputed maximum matching, this problem is modeled into recovering controllability of it after removing a known network vertex. Then, we recover controllability of the residual network by efficiently finding a maximum matching rather than recomputation. As a result, except for precomputing a maximum matching and the following removed vertex, the worst-case execution time of control recovery into the residual LTI physical system is linear.

For LTI control systems, we provide mathematical tools - in terms of Linear Matrix Inequalities - for computing outer ellipsoidal bounds on the reachable sets that attacks can induce in the system when they are subject to the physical limits of the actuators. Next, for a given set of dangerous states, states that (if reached) compromise the integrity or safe operation of the system, we provide tools for designing new artificial limits on the actuators (smaller than their physical bounds) such that the new ellipsoidal bounds (and thus the new reachable sets) are as large as possible (in terms of volume) while guaranteeing that the dangerous states are not reachable. This guarantees that the new bounds cut as little as possible from the original reachable set to minimize the loss of system performance. Computer simulations using a platoon of vehicles are presented to illustrate the performance of our tools.

Multi-robot transfer learning allows a robot to use data generated by a second, similar robot to improve its own behavior. The potential advantages are reducing the time of training and the unavoidable risks that exist during the training phase. Transfer learning algorithms aim to find an optimal transfer map between different robots. In this paper, we investigate, through a theoretical study of single-input single-output (SISO) systems, the properties of such optimal transfer maps. We first show that the optimal transfer learning map is, in general, a dynamic system. The main contribution of the paper is to provide an algorithm for determining the properties of this optimal dynamic map including its order and regressors (i.e., the variables it depends on). The proposed algorithm does not require detailed knowledge of the robots' dynamics, but relies on basic system properties easily obtainable through simple experimental tests. We validate the proposed algorithm experimentally through an example of transfer learning between two different quadrotor platforms. Experimental results show that an optimal dynamic map, with correct properties obtained from our proposed algorithm, achieves 60-70% reduction of transfer learning error compared to the cases when the data is directly transferred or transferred using an optimal static map.

This paper studies the stability of event-triggered control systems subject to Denial-of-Service attacks. An improved method is provided to increase frequency and duration of the DoS attacks where closed-loop stability is not destroyed. A two-mode switching control method is adopted to maintain stability of event-triggered control systems in the presence of attacks. Moreover, this paper reveals the relationship between robustness of systems against DoS attacks and lower bound of the inter-event times, namely, enlarging the inter-execution time contributes to enhancing the robustness of the systems against DoS attacks. Finally, some simulations are presented to illustrate the efficiency and feasibility of the obtained results.

Security of control systems have become a new and important field of research since malicious attacks on control systems indeed occurred including Stuxnet in 2011 and north eastern electrical grid black out in 2003. Attacks on sensors and/or actuators of control systems cause malfunction, instability, and even system destruction. The impact of attack may differ by which instrumentation (sensors and/or actuators) is being attacked. In particular, for control systems with multiple sensors, attack on each sensor may have different impact, i.e., attack on some sensors leads to a greater damage to the system than those for other sensors. To investigate this, we consider sensor bias injection attacks in linear control systems equipped with anomaly detector, and quantify the maximum impact of attack on sensors while the attack remains undetected. Then, we introduce a notion of sensor security index for linear dynamic systems to quantify the vulnerability under sensor attacks. Method of reducing system vulnerability is also discussed using the notion of sensor security index.

Zero dynamics attack is lethal to cyber-physical systems in the sense that it is stealthy and there is no way to detect it. Fortunately, if the given continuous-time physical system is of minimum phase, the effect of the attack is negligible even if it is not detected. However, the situation becomes unfavorable again if one uses digital control by sampling the sensor measurement and using the zero-order-hold for actuation because of the `sampling zeros.' When the continuous-time system has relative degree greater than two and the sampling period is small, the sampled-data system must have unstable zeros (even if the continuous-time system is of minimum phase), so that the cyber-physical system becomes vulnerable to `sampling zero dynamics attack.' In this paper, we begin with its demonstration by a few examples. Then, we present an idea to protect the system by allocating those discrete-time zeros into stable ones. This idea is realized by employing the so-called `generalized hold' which replaces the zero-order-hold.