Optimal Attack Schedule Research Articles

Optimal DoS Attack Scheduling for Cyber–Physical Systems With Channel Hopping Scheme

Optimal DoS Attack Scheduling for Cyber–Physical Systems With Channel Hopping Scheme

Optimal energy allocation based on SINR under DoS attack

According to signal to interference plus noise ratio (SINR) of channel, we consider optimal attack schedule against remote state estimation in cyber–physical systems (CPSs) under denial of service (DoS) attack. Each physical process has a smart sensor that acquires the measurement of the system and transmits its local state estimation to the remote estimation terminal through a wireless channel. At each time step, a DoS attacker can send a jamming attack to one of the two channels. On the side of the attacker, this paper aims to search an optimal strategy, which maximizes the estimation error of the remote estimator. We propose an algorithm to obtain the optimal attack schedule policy by using of Markov decision process (MDP). A numerical example is provided to demonstrate the effectiveness of the proposed methods.

Energy‐efficient DoS attack against remote state estimation

In this paper, the security issue in cyber‐physical system (CPS) is investigated. In order to maximize the attack effect and save the limited energy, the energy efficiency problem is investigated from the perspective of the jammer. This problem is established as a mixed‐integer programming problem firstly, and then a necessary condition is presented to explore the optimal energy for a given attack number. Moreover, an energy efficiency optimization (EEO) algorithm is proposed to derive the optimal attack schedule. Lastly, some numerical results are shown to validate the effectiveness of the proposed algorithm.

Optimal DoS attack scheduling for multi-sensor remote state estimation over interference channels

In this paper, we investigate the optimal denial-of-service attack scheduling problems in a multi-sensor case over interference channels. Multiple attackers aim to degrade the performance of remote state estimation under attackers’ energy constraints. The attack decision of one attacker may be affected by the others while all attackers find their own optimal strategies to degrade estimation performance. Consequently, the Markov decision process and Markov cooperative game in two different information scenarios are formulated to study the optimal attack strategies for multiple attackers. Because of the complex computations of the high-dimensional Markov decision process (Markov cooperative game) as well as the limited information for attackers, we propose a value iteration adaptive dynamic programming method to approximate the optimal solution. Moreover, the structural properties of the optimal solution are analyzed. In the Markov cooperative game, the optimal joint attack strategy which admits a Nash equilibrium is studied. Several numerical simulations are provided to illustrate the feasibility and effectiveness of the main results.

An Analysis on Optimal Attack Schedule Based on Channel Hopping Scheme in Cyber-Physical Systems.

In this paper, we investigate the issue of security on the remote state estimation in cyber-physical systems (CPSs), where a wireless sensor utilizes the channel hopping scheme to transmit the data to the remote estimator over multiple channels in the presence of periodic denial-of-service attacks. Assume that the jammer can interfere with a subset of channels at each attack time in active period. For an energy-constraint jammer, the problem of how to select the number of channels at each attack time to maximally deteriorate the CPS performance is investigated. Based on the index of average estimation error, we introduce two different attack strategies, which include selecting identical number of channels and unequal number of channels at each attack time, and further show theoretically that the attack effect by selecting unequal number of channels is better than that of selecting identical number of channels. By formulating the problem of selecting the number of channels as integer programming problems, we present the corresponding algorithm to approximate the optimal attack schedule for both cases. The numerical results are presented to validate the theoretical results and the effectiveness of the proposed algorithms.

Optimal Stealthy Linear-Attack Schedules on Remote State Estimation

In this paper, we address optimal schedule issue of a linear attacker without being detected by $\chi ^2$ detector. Due to limited energy, the attacker needs to decide whether to launch attacks at each step and design optimal attack strategy over a finite-time horizon. To address it, we take average error (AE) and terminal error (TE) as indices. After analyzing AEs under three special types of schedules and studying monotonic property of TE with respect to attack time instants, the optimal attack schedules for AE and TE are respectively determined theoretically. Besides, we further investigate optimal attack schedule for multiple subsystems. The accomplished results well extend the existing work in false data attacks without optimal structure and promote the linear-attack in dynamical systems to the optimal schedule issue. Illustrative examples are also given to validate our theoretical results.

Optimal cooperative multiple-attackers scheduling against remote state estimation of cyber-physical systems

Abstract In this paper, we consider multiple-attackers schedule problem against remote state estimation in cyber-physical systems (CPSs). Compared with the existing results in which only one type of attacker is considered, we aim to address the case that Denial-of-Service (DoS) attacker and linear deception attacker exist in CPSs simultaneously. With limited resource, the two attackers have to, cooperatively, decide whether to launch or not and which type of attack to inject at each time and further determine optimal schedule over a finite time horizon to degrade the performance of system at the largest. First of all, the evolutions of remotely estimated state and error covariance under an attack schedule are derived. Next, we regard average error and terminal error as performance indexes of systems, respectively, and analyze their intrinsic properties to find out the corresponding optimal attack scheduling schemes. Finally, an example is given to show the effectiveness of our theoretical results.

Optimizing Attack Schedules Based on Energy Dispatch Over Two-Hop Relay Networks

In this article, the security issue of remote state estimation in cyber-physical systems (CPS) for a two-hop relay network is investigated. As the system performance depends on communication topology and communication environment over each channel, we explore the channel selection problem to maximize the attack effect, from the perspective of the jammer. Furthermore, for an energy-constrained jammer, there exists the optimal strategy to decide the attack number and the dropout rate, since the amount of attack number decreases and the dropout rate increases when the energy launched at each attack time becomes larger. For this consideration, the problem of energy dispatch, aiming to derive the optimal tradeoff between the attack number and the energy launched at each attack time, is studied along with the channel selection problem. We first formulate this problem as a mixed integer programming problem to derive the optimal attack schedule including the channel selection, the attack number, and the corresponding energy dispatch. Then, using the optimality equations based on the Markov decision process allows us to present the characteristics of the optimal energy dispatch policy for a given attack number, and further propose the dynamic energy dispatch algorithm with low complexity to approximate the optimal schedule. Besides, for the constant dispatch (CD) case, the optimum solution in an analytical form for the channel selection problem can be obtained, and we thus present a CD algorithm to acquire the optimal schedule. Last, numerical results are given to validate the theoretical findings and the effectiveness of the proposed algorithms.

Optimal Jamming Attack Scheduling of Interactive Channels

Recently, public attention is thoroughly aroused as to the security threats of Cyber-Physical Systems (CPS), which can seriously disrupt the system operation. In order to analyze the impact of potential cyber-attacks, one needs to investigate the attack scheduling strategy from the attacker's perspective. In this paper, we investigate the optimal attack schedules to degrade the system performance through multiple interactive channels against remote state estimation, which is different from the studies through multiple independent channels. Specifically, a channel is affected when the attacker launches an attack on another one, causing two different loss rates of the data package. Based on this, we represent the estimation error covariance of the remote estimator. Then we give the optimal jamming attack schedule theoretically. Finally, the effectiveness of the theoretical results is shown by numerical simulations.

Optimal Attack Schedule for Two Sensors State Estimation Under Jamming Attack

In this paper, we investigate stable state estimation and optimal attack schedule problems of the wireless Cyber-Physical Systems (CPS) with two sensors under Denial-of-Service (DoS) attack. At each sampling time, a DoS attacker can conduct jamming attack in a certain frequency band to jam the two wireless packet dropping channels and cause packet dropouts. Due to the different frequency bandwidths of the two channels, one and only one channel is jammed by the jamming attack at each time step. A sufficient condition is presented to ensure the stability of the state estimation based on the Kalman filter. And the optimal attack schedule, which maximizes the expected average estimation error at the remote estimator, is proposed in the viewpoint of the attacker. Moreover, when there is a special intrusion detection system (IDS) at the estimator, the optimal attack schedule is also provided. A numerical simulation is given out to illustrate the effectiveness of the obtained results.

Optimal jamming attack schedule for remote state estimation with two sensors

In cyber-physical systems (CPS), cyber threats emerge in many ways which can cause significant destruction to the system operation. In wireless CPS, adversaries can block the communications of useful information by channel jamming, incurring the so-called denial of service (DoS) attacks. In this paper, we investigate the problem of optimal jamming attack scheduling against remote state estimation wireless network. Specifically, we consider that two wireless sensors report data to a remote estimator through two wireless communication channels lying in two unoverlapping frequency bands, respectively. Meanwhile, an adversary can select one and only one channel at a time to execute jamming attack. We prove that the optimal attack schedule is continuously launching attack on one channel determined based on the system dynamics matrix. The theoretical results are validated by numerical simulations.

Optimal Denial-of-Service Attack Scheduling With Energy Constraint Over Packet-Dropping Networks

The recent years have seen a surge of security issues of cyber-physical systems (CPS). In this paper, denial-of-service (DoS) attack scheduling is investigated in depth. Specifically, we consider a system where a remote estimator receives the data packet sent by a sensor over a wireless network at each time instant, and an energy-constrained attacker that cannot launch DoS attacks all the time designs the optimal DoS attack scheduling to maximize the attacking effect on the remote estimation performance. Most of the existing works concerning DoS attacks focus on the ideal scenario in which data packets can be received successfully if there is no DoS attack. To capture the unreliability nature of practical networks, we study the packet-dropping network in which packet dropouts may occur even in the absence of attack. We derive the optimal attack scheduling scheme that maximizes the average expected estimation error, and the one which maximizes the expected terminal estimation error over packet-dropping networks. We also present some countermeasures against DoS attacks, and discuss the optimal defense strategy, and how the optimal attack schedule can serve for more effective and resource-saving countermeasures. We further investigate the optimal attack schedule with multiple sensors. The optimality of the theoretical results is demonstrated by numerical simulations.

Energy efficient jamming attack schedule against remote state estimation in wireless cyber-physical systems

Recently, there has been a growing volume of literature on the security aspect of wireless cyber-physical systems (CPS). Remote state estimation through wireless channels is a representative application of wireless CPS. However, such a system is exposed to various cyber security threats, such as replay attacks, jamming attacks and bad data injection attacks. In this paper, we focus on the wireless jamming attack and examine, from the standpoint of the attacker, the problem of optimal attack schedule that causes the largest performance degradation of the remote state estimation system, subject to attacker’s energy constraint. Unlike some existing studies, we consider estimating multiple systems where sensors transmitting data to the remote estimator through multiple independent wireless channels. Due to the attacker’s radio constraint, we assume that it can only launch jamming attack at one of the channels at any time. We start with the two-system case and formulate the energy efficient jamming attack schedule problem as a nonlinear program. The optimal energy efficient schedule is theoretically derived and is shown dependent on the wireless channels’ properties, energy budget of the attacker and dynamics of the systems to be estimated. Then, we extend the results to multi-system cases, and propose both an optimal schedule algorithm and an efficient algorithm of much lower complexity. Finally, we validate the theoretical results by numerical simulations.

Optimal DoS Attack Scheduling in Wireless Networked Control System

Recently, many literature works have considered the security issues of wireless networked control system (WNCS). However, few works studied how the attacker should optimize its attack schedule in order to maximize the effect on the system performance due to the insufficiency of energy at the attacker side. This paper fills this gap from the aspect of control system performance. We consider the optimal jamming attack that maximizes the Linear Quadratic Gaussian (LQG) control cost function under energy constraint. After analyzing the properties of the cost function under an arbitrary attack schedule, we derive the optimal jamming attack schedule and the corresponding cost function. System stability under this optimal attack schedule is also considered. We further investigate the optimal attack schedule in a WNCS with multiple subsystems. Different examples are provided to demonstrate the effectiveness of the proposed optimal denial-of-service attack schedule.

Optimal Jamming Attack Scheduling in Networked Sensing and Control Systems

This paper investigates the optimal jamming attack scheduling in Networked Sensing and Control Systems (NSCS). From viewpoint of the attacker, we formulate an optimization problem which maximizes the Linear Quadratic Gaussian (LQG) control cost with attacking energy constraint in a finite time horizon. For two special cases, we obtain that the optimal jamming attack schedule is to consecutively attack in the given time horizon. For the general case, we propose an algorithm to find the optimal schedules. Finally, we study the effectiveness of our proposed attack strategies on our established semiphysical testbed.