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1.
This paper is concerned with a security problem about malicious integrity attacks in state estimation system, in which multiple smart sensors locally measure information and transmit it to a remote fusion estimator though wireless channels. A joint constraint is considered for the attacker behaviour in each channel to keep stealthiness under a residual-based detector on the remote side. In order to degrade the estimator performance, the attacker will maximize the trace of the remote state estimation error covariance which is derived based on Kalman filter theory. It is proved that the optimal linear attack strategy design problem is convex and finally turned into a semi-definite programming problem. In addition, the tendency of attack behaviour on recursive and fixed Kalman filter system is analyzed. Several examples are given to illustrate the theoretical results.  相似文献   

2.
In this paper, we study the problem of remote state estimation on networks with random delays and unavailable packet sequence due to malicious attacks. Two maximum a posteriori (MAP) schemes are proposed to detect the unavailable packet sequence. The first MAP strategy detects the packet sequence using data within a finite time horizon; the second MAP strategy detects the packet sequence by a recursive structure, which effectively reduces the computation time. With the detected packet sequence, we further design a linear minimum mean-squared error (LMMSE) estimation algorithm based on smoothing techniques, rather than using the classic prediction and update structure. A wealth of information contained in the combined measurements is utilized to improve the estimation performance. Finally, the effectiveness of the proposed algorithms is demonstrated by simulation experiments.  相似文献   

3.
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.  相似文献   

4.
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5.
Unpredictable packet loss that occurs in the channel connecting a local sensor and a remote estimator will deteriorate the performance of state estimation. To relieve this detrimental impact, an online linear temporal coding scheme is studied in this paper. If the packet of the last step is lost, a linear combination of the current and the last measurements with proper weights is transmitted; otherwise, only the current data is sent. By virtue of the innovation sequence approach, a linear minimum mean-squared error estimation algorithm is designed. To optimize performance, a novel estimator is also proposed which provides a recursive expression of the error covariances. The proposed two algorithms are proved to be equivalent via a set of transformations. With the aid of some optimization techniques, a recursive algorithm is presented to obtain the optimal coding weight in terms of minimizing the average estimation error covariance.  相似文献   

6.
The popularity of Twitter for information discovery, coupled with the automatic shortening of URLs to save space, given the 140 character limit, provides cybercriminals with an opportunity to obfuscate the URL of a malicious Web page within a tweet. Once the URL is obfuscated, the cybercriminal can lure a user to click on it with enticing text and images before carrying out a cyber attack using a malicious Web server. This is known as a drive-by download. In a drive-by download a user's computer system is infected while interacting with the malicious endpoint, often without them being made aware the attack has taken place. An attacker can gain control of the system by exploiting unpatched system vulnerabilities and this form of attack currently represents one of the most common methods employed. In this paper we build a machine learning model using machine activity data and tweet metadata to move beyond post-execution classification of such URLs as malicious, to predict a URL will be malicious with 0.99 F-measure (using 10-fold cross-validation) and 0.833 (using an unseen test set) at 1 s into the interaction with the URL. Thus, providing a basis from which to kill the connection to the server before an attack has completed and proactively blocking and preventing an attack, rather than reacting and repairing at a later date.  相似文献   

7.
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.  相似文献   

8.
In this paper, the state estimation problem for discrete-time networked systems with communication constraints and random packet dropouts is considered. The communication constraint is that, at each sampling instant, there is at most one of the various transmission nodes in the networked systems is allowed to access a shared communication channel, and then the received data are transmitted to a remote estimator to perform the estimation task. The channel accessing process of those transmission nodes is determined by a finite-state discrete-time Markov chain, and random packet dropouts in remote data transmission are modeled by a Bernoulli distributed white sequence. Using Bayes’ rule and some results developed in this study, two state estimation algorithms are proposed in the sense of minimum mean-square error. The first algorithm is optimal, which can exactly compute the minimum mean-square error estimate of system state. The second algorithm is a suboptimal algorithm obtained under a lot of Gaussian hypotheses. The proposed suboptimal algorithm is recursive and has time-independent complexity. Computer simulations are carried out to illustrate the performance of the proposed algorithms.  相似文献   

9.
《Journal of The Franklin Institute》2022,359(18):10726-10740
In this paper, the secure transmission issue of a remote estimation sensor network against eavesdropping is studied. A powerful eavesdropper overhears the measurement data sent through the communication channels between the sensors and the remote estimator, and estimates system state illegally, which threatens the system information security. Different from the existing anti-eavesdropping design approaches, a stealthy artificial noise (AN) strategy is proposed to prevent eavesdroppers from deciphering encryption policy by hiding the encryption process from eavesdroppers. It has the same dynamical process with each sensor’s measurement to guarantee that the estimation error of the eavesdropper is unbounded while its observation residual variance keeps in certain bound and converges to 0, and further ensure system security without alerting the eavesdropper. It is proved that the strategy is feasible whenever the eavesdropper starts to wiretap. The selection of sensors that needs to be encrypted is further given by solving an optimization problem. The effectiveness of the proposed algorithm is verified by two simulation examples.  相似文献   

10.
This paper studies the asynchronous state fusion estimation problem for multi-sensor networked systems subject to stochastic data packet dropouts. A set of Bernoulli sequences are adopted to describe the random packet losses with different arriving probabilities for different sensor communication channels. The asynchronous sensors considered in this paper can have arbitrary sampling rates and arbitrary initial sampling instants, and may even sample the system non-uniformly. Asynchronous measurements collected within the fusion interval are transformed to the fusion time instant as a combined equivalent measurement. An optimal asynchronous estimation fusion algorithm is then derived based on the transformed equivalent measurement using the recursive form of linear minimum mean squared error (LMMSE) estimator. Cross-correlations between involved random variables are carefully calculated with the stochastic data packet dropouts taken into account. A numerical target tracking example is provided to illustrate the feasibility and effectiveness of the proposed algorithm.  相似文献   

11.
This paper investigates the multi-channel transmission scheduling problem for remote state estimation based on a hopping scheme in cyber-physical systems. The smart sensor sends multiple subpackets over different orthogonal channels to the remote end simultaneously. Owing to the randomness and vulnerability of transmission environments, the uncertain multi-channel states are considered in this paper, which relaxes the assumption of existing deterministic models. The objective is to find an appropriate hopping scheme that minimizes the remote estimation error covariance. First, the multi-channel selection problem is modeled as a multi-arm bandits (MAB) matrix via taking the packet receiving probability as the gain. From the perspective of strategy and channel, two exponential-weight online learning algorithms are designed with the assistance of transmission energy switching policy. Then, based on Bernstein’s inequality for martingales and mini-batching loop, the upper bounds of algorithms’ regret values are analyzed under stochastic and adversarial channel states, respectively. Further, the estimator expression in iterative form and a sufficient condition for the error covariance to be bounded are derived. Finally, an example of unmanned vehicle moving demonstrates all the theoretical results.  相似文献   

12.
《Journal of The Franklin Institute》2019,356(17):10593-10607
This paper investigates the problem of a multi-rate networked system estimation with considering random and malicious packet losses. Three different rates are used: system sampling rate, measurement updating rate and estimation updating rate. Thus, the network energy can be saved. Since the plant and filtering are connected via network channel, the data packet losses unavoidably happen. In order to study the combination of the random and malicious packet losses, the probabilistic characterization for the link failures is applied, which leads to a stochastic estimation error system. The almost surely exponentially stability criteria is applied to guarantee this stochastic system stable. Finally, a cloud-aided vehicle suspension system is applied to verify the theoretical finding.  相似文献   

13.
In this paper, the event-triggered distributed multi-sensor data fusion algorithm is presented for wireless sensor networks (WSNs) based on a new event-triggered strategy. The threshold of the event is set according to the chi-square distribution that is constructed by the difference of the measurement of the current time and the measurement of the last sampled moment. When the event-triggered decision variable value is larger than the threshold, the event is triggered and the observation is sampled for state estimation. In designing the dynamic event-triggered strategy, we relate the threshold with the quantity in the chi-square distribution table. Therefore, compared to the existed event-triggered algorithms, this novel event-triggered strategy can give the specific sampling/communication rate directly and intuitively. In addition, for the presented distributed fusion in wireless sensor networks, only the measurements in the neighborhood (i.e., the neighbor nodes and the neighbor’s neighbor nodes) of the fusion center are fused so that it can obtain the optimal state estimation under limited energy consumption. A numerical example is used to illustrate the effectiveness of the presented algorithm.  相似文献   

14.
In this paper, the problem about the false data injection attacks on sensors to degrade the state estimation performance in cyber-physical systems(CPSs) is investigated. The attack strategies for unstable systems and stable ones are both designed. For unstable systems, based on the idea of zero dynamics, an unbounded attack strategy is proposed which can drive the state estimation error variations to infinity. The proposed method is more general than existing unbounded attack strategies since it relaxes the requirement for the initial value of the estimation error. For stable systems, it is difficult to bring unbounded impacts on the estimation error variations. Therefore, in this case, an attack strategy with adjustable attack performance which makes the estimation error variations track predesigned target values is proposed. Furthermore, a uniform attack strategy which aims to deteriorate state estimation for both stable systems and unstable ones is derived. Finally, simulations are provided to illustrate the effectiveness of the proposed attack strategies.  相似文献   

15.
In this paper, a data-driven covert attack strategy is proposed for a class of closed-loop cyber-physical systems. Without the parameters of the system plant and the nominal controller, the attacker can only use the intercepted input and output data of the nominal system. The injected input attack signals are designed based on the subspace predictive control method, which can deviate the real outputs to the expected attack references in a future time horizon. Meanwhile, by injecting the designed output attack signals for compensation, the attack cannot be detected by the anomaly detector. The simulation results of an irrigation canal system illustrate the effect of the proposed strategy with satisfactory performances.  相似文献   

16.
This paper aims to create a secure environment for state estimation and control design of a networked system composed of multiple dynamic entities and remote computational units, in the presence of disclosure attacks. In particular, both dynamic entities and computational units may be vulnerable to attacks and become malicious. The objective is to ensure that the input and output data of the benign entities are protected from the malicious parties as well as protected when they are transmitted over the network in a distributed environment. We propose a methodology integrating a novel double-layer cryptographic technique with an observer-based control algorithm to achieve the objective where the cryptographic technique addresses the security requirements and the control algorithm satisfies the performance requirements.  相似文献   

17.
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18.
We consider a remote state estimation process under an active eavesdropper for cyber-physical system. A smart sensor transmits its local state estimates to a remote estimator over an unreliable network, which is eavesdropped by an adversary. The intelligent adversary can work in passive eavesdropping mode and active jamming mode. An active jamming mode enables the adversary to interfere the data transmission from sensor to estimator, and meanwhile improve the data reception of itself. To protect the transmission data from being wiretapped, the sensor with two antennas injects noise to the eavesdropping link with different power levels. Aiming at minimizing the estimation error covariance and power cost of themselves while maximizing the estimation error covariance of their opponents, a two-player nonzero-sum game is constructed for sensor and active eavesdropper. For an open-loop case, the mixed Nash equilibrium is obtained by solving an one-stage nonzero-sum game. For a long term consideration, a Markov stochastic game is introduced and a Nash Q-learning method is given to find the Nash equilibrium strategies for two players. Numerical results are provided to show the effectiveness of our theoretical conclusions.  相似文献   

19.
In this paper, we focus on an output secure consensus control issue for nonlinear multi-agent systems (MASs) under sensor and actuator attacks. Followers in an MAS are in strict-feedback form with unknown control directions and unknown dead-zone input, where both sensors and nonlinear characteristics of dead-zone in actuators are paralyzed by malicious attacks. To deal with sensor attacks, uncertain dynamics in individual follower are separated by a separation theorem, and estimation parameters are introduced for compensating and mitigating the influence from adversaries. The influence from actuator attacks are treated as a total displacement in a dead-zone nonlinearity, and an upper bound, as well as its estimation, is introduced for this displacement. The dead-zone nonlinearity, sensor attacks and unknown control gains are gathered together regarded as composite unknown control directions, and Nussbaum functions are utilized to address the issue of unknown control directions. A distributed secure consensus control strategy is thus developed recursively for each follower in the framework of surface control method. Theoretically, the stability of the closed-loop MAS is analyzed, and it is proved that the MAS achieves output consensus in spite of nonlinear dynamics and malicious attacks. Finally, theoretical results are verified via a numerical example and a group of electromechanical systems.  相似文献   

20.
《Journal of The Franklin Institute》2021,358(18):10079-10094
This paper is focused on the distributed estimation issue in the form of set-membership (SM) for a class of discrete time-varying systems suffering mix-time-delays and state-saturations. The phenomena of time-delays and state-saturations are introduced to better describe insightful engineering. During local measurements transmission between sensors over a resource-limited sensor network, to prevent data collisions and resource-consumption, a newly dynamic event-triggering strategy (DETS) is designed to dispatch the local measurements transmission for each sensor to its neighbors. Compared with the most existing static ETSs, this DETs can mitigate the total number of triggering times and enlarge interval time between consecutive triggering instants. Then, some novel adequate criteria for designing the desired event-based SM estimators are derived such that the plant’s true state always resides in each sensor’s ellipsoidal region regardless of the simultaneous presence of bounded noises, mixed time delays and state-saturations. Subsequently, a recursive optimization algorithm is formulated such that the minimal ellipsoids, the estimators gains and event-triggering weighted matrices are acquired simultaneously. A verification simulation is presented to illustrate the advantages of the design approach of the developed state estimator.  相似文献   

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