Article
Computer Science, Information Systems
Xiao-Guang Zhang, Guang-Hong Yang
Summary: This paper investigates stealthy attack problems in CPSs under the scheduling effects of the RRP, proposing a new attack model to overcome protocol-induced effects and obtaining the optimal attack strategy by solving an SDP problem.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Information Systems
Weihao Song, Zidong Wang, Jianan Wang, Jiayuan Shan
Summary: This paper investigates a particle filtering algorithm based on Round-Robin protocol for handling general nonlinear cyber-physical systems with non-Gaussian noises and randomly occurring deception attacks. The algorithm is shown to effectively prevent data collisions and reduce communication overhead, demonstrating feasibility and effectiveness in target tracking problems.
INFORMATION SCIENCES
(2021)
Article
Automation & Control Systems
Bo Wu, Xiao-Heng Chang
Summary: This paper focuses on the security control problem for nonlinear systems with the effects of quantization, communication protocol, and deception attacks based on the Takagi-Sugeno (T-S) fuzzy model. By designing a mode-dependent observer-based controller and dynamic quantizers, the probability security of the closed-loop system is guaranteed.
Article
Automation & Control Systems
Wei Xing, Xudong Zhao, Ning Zhao, Guangdeng Zong, Ben Niu, Ning Xu
Summary: In this study, we analyze optimal denial-of-service (DoS) attacks for remote estimation in a two-hop network. The measurements from sensors are transmitted to a remote estimator through a relay, which can be congested by a malicious attacker. We propose an optimal attack schedule considering the scenario where the attacker can interfere with both wireless communication channels simultaneously during the attack period, and we demonstrate the theoretical results with numerical examples.
SYSTEMS & CONTROL LETTERS
(2023)
Article
Automation & Control Systems
Meng Li, Yong Chen, Yuezhi Liu
Summary: This paper addresses the secure control strategy design issue for jump cyber-physical systems (CPSs) with malicious attacks, and presents a secure control strategy based on robust sliding-mode control (SMC). By constructing an integral sliding-mode hyperplane, solving the slide-mode parameters, and proposing a robust sliding-mode controller, the approach effectively deals with malicious attacks in CPSs.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Automation & Control Systems
Zhina Zhang, Yugang Niu, Hamid Reza Karimi
Summary: This article investigates a sliding mode control (SMC) design problem for a class of discrete-time interval type-2 fuzzy systems where sensors are scheduled by a round-Robin communication protocol. A compensation scheme is proposed for other sensor nodes, based on which a token-dependent sliding mode controller is synthesized. Sufficient conditions are derived to ensure system states can reach a neighborhood of the sliding surface, resulting in an input-to-state stable closed-loop fuzzy system. Simulation results validate the effectiveness of the proposed SMC method.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Automation & Control Systems
Lijuan Zha, Tao Huang, JinLiang Liu, Xiangpeng Xie, Engang Tian
Summary: In this study, the security quantized control problem is investigated for discrete-time Takagi-Sugeno (T-S) fuzzy systems with deception attacks based on the multi-channel-enabled round-robin (MCERR) protocol. A new system model is established considering random deception attacks and measurement outliers, and a sufficient condition is derived for system stability. An outlier resistant observer-based controller is developed to mitigate the impact of deception attacks, and the expressions of observer gains and controller gains are obtained. The proposed method's effectiveness is validated through simulation results.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Shamila Nateghi, Yuri Shtessel, Christopher Edwards
Summary: This article investigates the resilient control of linear cyber-physical systems with cyber-attacked sensor measurements and actuator commands. It achieves online reconstruction of unknown cyber-attacks and proposes cleaning up the attacked/corrupted sensor measurements and actuators, showing that the system retains its performance prior to the attacks after a transient response for attack reconstruction. The efficacy of the proposed algorithms is demonstrated on an electrical power network.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Mathematics, Applied
Ning Zhang, Wenhai Qi, Guocheng Pang, Jun Cheng, Kaibo Shi
Summary: This paper discusses the observer-based sliding mode control for fuzzy stochastic semi-Markov switching systems (S-MSSs) under cyber attacks. Conditions are established to achieve stochastic stability for the fuzzy sliding mode dynamics, considering deception attacks. The proposed controller guarantees the reachability of the sliding region and is validated through simulation study on a single-link robot arm model.
APPLIED MATHEMATICS AND COMPUTATION
(2022)
Article
Automation & Control Systems
Yuhang Jin, Xiaosen Ma, Xueyang Meng, Yun Chen
Summary: This paper investigates the design problem of distributed mixed H-2/H-8 fusion filter for cyber-physical systems under non-ideal measurements and Round-Robin protocol. The Round-Robin protocol is used to schedule the data transmissions and save communication resources. The measurement considers noises, random saturations, nonlinearity perturbations, and packet dropouts. The objective is to propose a fusion filtering method that ensures prescribed performance constraints on the local and fusion filtering error dynamics.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2023)
Article
Computer Science, Information Systems
Abbas Nemati, Mansour Peimani, Saleh Mobayen, Sayyedjavad Sayyedfattahi
Summary: This study proposes a novel adaptive non-singular Terminal Sliding Mode (TSM) control procedure for the speedy and finite time stabilization of nonlinear Cyber-Physical Systems (CPSs). The proposed method eliminates the reaching phase and improves the robustness of the entire system. The online adaptive laws effectively deal with unwanted disturbances, actuator cyber-attacks, and time-varying delays without the need to recognize their upper bounds.
INFORMATION SCIENCES
(2022)
Article
Automation & Control Systems
Zhihui Wu, Siteng Ma, Cai Chen, Dongyan Chen, Xue Zhao
Summary: This paper addresses the problem of dissipative fault detection for nonlinear Markov jump systems with cyber attacks and hidden modal information. The round-robin protocol is introduced to save network bandwidth and two Bernoulli random variables are used to characterize the measurement affected by potential cyber attacks. The hidden Markov model is employed to handle the phenomenon of hidden mode information. Sufficient conditions based on Lyapunov stability theory are derived to ensure stochastic stability and stochastic strict dissipativity of the FD system. The desired FD filter matrices are obtained through solving linear matrix inequalities. A simulation is provided to verify the feasibility and effectiveness of the designed FD scheme.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Hui Shang, Guangdeng Zong, Wenhai Qi
Summary: In this study, a security control method for networked discrete-time semi-Markov jump systems is investigated, taking into account deception attacks and round-robin protocol. By establishing an observer-based security control scheme and designing controller and observer parameters using linear matrix inequalities, the mean-square stability of the system with o-error is ensured. Theoretical results are validated using a F-404 aircraft engine model.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2022)
Article
Automation & Control Systems
Ji-Jing Lu, Xiao-Heng Chang
Summary: This paper focuses on the problem of mixed H-8 and passive resilient control for uncertain discrete-time networked control systems subject to time delays. The measurement output is quantized by a dynamic quantizer and transmitted through an unreliable communication channel where deception attacks may occur randomly. The Round-Robin (RR) protocol is adopted to schedule sensors in a predetermined transmission order to reduce communication burden. A new performance index is developed to solve the restriction of the same dimension of control output and the exogenous disturbance. The paper presents sufficient conditions for the resilient controller and the dynamic quantizer, improving the robustness and stability of the resulting closed-loop system.
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
(2023)
Article
Automation & Control Systems
Bin Wei, Engang Tian, Jinliang Liu, Xia Zhao
Summary: The study focuses on the probabilistic-constrained tracking control issue for a class of time-varying non-linear stochastic systems with sensor saturation, deception attacks, and limited bandwidth. It utilizes RLMIs to estimate the state and design the tracking controller while arranging the transmission order of measurements using the RR protocol.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Computer Science, Information Systems
Xia Liang, Jie Guo, Peide Liu
Summary: This paper investigates a novel consensus model based on social networks to manage manipulative and overconfident behaviors in large-scale group decision-making. By proposing a novel clustering model and improved methods, the consensus reaching is effectively facilitated. The feedback mechanism and management approach are employed to handle decision makers' behaviors. Simulation experiments and comparative analysis demonstrate the effectiveness of the model.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Xiang Li, Haiwang Guo, Xinyang Deng, Wen Jiang
Summary: This paper proposes a method based on class gradient networks for generating high-quality adversarial samples. By introducing a high-level class gradient matrix and combining classification loss and perturbation loss, the method demonstrates superiority in the transferability of adversarial samples on targeted attacks.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Lingyun Lu, Bang Wang, Zizhuo Zhang, Shenghao Liu
Summary: Many recommendation algorithms only rely on implicit feedbacks due to privacy concerns. However, the encoding of interaction types is often ignored. This paper proposes a relation-aware neural model that classifies implicit feedbacks by encoding edges, thereby enhancing recommendation performance.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Jaehong Yu, Hyungrok Do
Summary: This study discusses unsupervised anomaly detection using one-class classification, which determines whether a new instance belongs to the target class by constructing a decision boundary. The proposed method uses a proximity-based density description and a regularized reconstruction algorithm to overcome the limitations of existing one-class classification methods. Experimental results demonstrate the superior performance of the proposed algorithm.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Hui Tu, Shifei Ding, Xiao Xu, Haiwei Hou, Chao Li, Ling Ding
Summary: Border-Peeling algorithm is a density-based clustering algorithm, but its complexity and issues on unbalanced datasets restrict its application. This paper proposes a non-iterative border-peeling clustering algorithm, which improves the clustering performance by distinguishing and associating core points and border points.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Long Tang, Pan Zhao, Zhigeng Pan, Xingxing Duan, Panos M. Pardalos
Summary: In this work, a two-stage denoising framework (TSDF) is proposed for zero-shot learning (ZSL) to address the issue of noisy labels. The framework includes a tailored loss function to remove suspected noisy-label instances and a ramp-style loss function to reduce the negative impact of remaining noisy labels. In addition, a dynamic screening strategy (DSS) is developed to efficiently handle the nonconvexity of the ramp-style loss.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Raghunathan Krishankumar, Sundararajan Dhruva, Kattur S. Ravichandran, Samarjit Kar
Summary: Health 4.0 is gaining global attention for better healthcare through digital technologies. This study proposes a new decision-making framework for selecting viable blockchain service providers in the Internet of Medical Things (IoMT). The framework addresses the limitations in previous studies and demonstrates its applicability in the Indian healthcare sector. The results show the top ranking BSPs, the importance of various criteria, and the effectiveness of the developed model.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Tao Tan, Hong Xie, Liang Feng
Summary: This paper proposes a heterogeneous update idea and designs HetUp Q-learning algorithm to enlarge the normalized gap by overestimating the Q-value corresponding to the optimal action and underestimating the Q-value corresponding to the other actions. To address the limitation, a softmax strategy is applied to estimate the optimal action, resulting in HetUpSoft Q-learning and HetUpSoft DQN. Extensive experimental results show significant improvements over SOTA baselines.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Chao Yang, Xianzhi Wang, Lina Yao, Guodong Long, Guandong Xu
Summary: This paper proposes a dynamic transformer-based architecture called Dyformer for multivariate time series classification. Dyformer captures multi-scale features through hierarchical pooling and adaptive learning strategies, and improves model performance by introducing feature-map-wise attention mechanisms and a joint loss function.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Xiguang Li, Baolu Feng, Yunhe Sun, Ammar Hawbani, Saeed Hammod Alsamhi, Liang Zhao
Summary: This paper proposes an enhanced scatter search strategy, using opposition-based learning, to solve the problem of automated test case generation based on path coverage (ATCG-PC). The proposed ESSENT algorithm selects the path with the lowest path entropy among the uncovered paths as the target path and generates new test cases to cover the target path by modifying the dimensions of existing test cases. Experimental results show that the ESSENT algorithm outperforms other state-of-the-art algorithms, achieving maximum path coverage with fewer test cases.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Shirin Dabbaghi Varnosfaderani, Piotr Kasprzak, Aytaj Badirova, Ralph Krimmel, Christof Pohl, Ramin Yahyapour
Summary: Linking digital accounts belonging to the same user is crucial for security, user satisfaction, and next-generation service development. However, research on account linkage is mainly focused on social networks, and there is a lack of studies in other domains. To address this, we propose SmartSSO, a framework that automates the account linkage process by analyzing user routines and behavior during login processes. Our experiments on a large dataset show that SmartSSO achieves over 98% accuracy in hit-precision.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Renchao Wu, Jianjun He, Xin Li, Zuguo Chen
Summary: This paper proposes a memetic algorithm with fuzzy-based population control (MA-FPC) to solve the joint order batching and picker routing problem (JOBPRP). The algorithm incorporates batch exchange crossover and a two-level local improvement procedure. Experimental results show that MA-FPC outperforms existing algorithms in terms of solution quality.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Guoxiang Zhong, Fagui Liu, Jun Jiang, Bin Wang, C. L. Philip Chen
Summary: In this study, we propose the AMFormer framework to address the problem of mixed normal and anomaly samples in deep unsupervised time-series anomaly detection. By refining the one-class representation and introducing the masked operation mechanism and cost sensitive learning theory, our approach significantly improves anomaly detection performance.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Jin Zhou, Kang Zhou, Gexiang Zhang, Ferrante Neri, Wangyang Shen, Weiping Jin
Summary: In this paper, the authors focus on the issue of multi-objective optimisation problems with redundant variables and indefinite objective functions (MOPRVIF) in practical problem-solving. They propose a dual data-driven method for solving this problem, which consists of eliminating redundant variables, constructing objective functions, selecting evolution operators, and using a multi-objective evolutionary algorithm. The experiments conducted on two different problem domains demonstrate the effectiveness, practicality, and scalability of the proposed method.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Georgios Charizanos, Haydar Demirhan, Duygu Icen
Summary: This article proposes a new fuzzy logistic regression framework that addresses the problems of separation and imbalance while maintaining the interpretability of classical logistic regression. By fuzzifying binary variables and classifying subjects based on a fuzzy threshold, the framework demonstrates superior performance on imbalanced datasets.
INFORMATION SCIENCES
(2024)