Article
Computer Science, Information Systems
Juan Ospina, Venkatesh Venkataramanan, Charalambos Konstantinou
Summary: Power systems are becoming cyber-physical energy systems (CPES) as a result of the integration of communication and IoT devices. Evaluating CPES security is challenging due to the lack of holistic consideration of the physical and cyber layers. This article proposes a metric, CPES-QSM, to quantify the interaction between the cyber and physical layers and suggests a method for incorporating this metric into operational decisions.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Telecommunications
Dan Wang, Bin Song, Yingjie Liu, Mingjun Wang
Summary: This paper aims to minimize system latency, considering security and reliability requirements, by proposing a distributed blockchain-assisted CPIoTS and an efficient resource allocation algorithm PPO-SRRA for edge-cloud computing coupled with CPS.
DIGITAL COMMUNICATIONS AND NETWORKS
(2022)
Article
Mathematics
Mahmoud Ragab, Sultanah M. Alshammari, Louai A. Maghrabi, Dheyaaldin Alsalman, Turki Althaqafi, Abdullah AL-Malaise AL-Ghamdi
Summary: The Internet of Things (IoT) is a network of interconnected physical devices that exchange and collect information. While IoT devices offer numerous advantages, they also pose security risks. Distributed Denial of Service (DDoS) attacks, in particular, exploit IoT devices to disrupt services. Therefore, there is a need for robust detection systems using artificial intelligence (AI) to identify these attacks.
Article
Engineering, Multidisciplinary
Juntao Chen, Corinne Touati, Quanyan Zhu
Summary: The IoT enables multi-layer system architectures in infrastructures, facilitating real-time information delivery and high-level situational awareness. However, due to wireless communications, IoT infrastructures face cybersecurity threats.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2021)
Article
Chemistry, Analytical
Lakshmana Kumar Ramasamy, Firoz Khan, Mohammad Shah, Balusupati Veera Venkata Siva Prasad, Celestine Iwendi, Cresantus Biamba
Summary: This paper discusses the evolution from the Internet of Computers to the Internet of Things and the challenges it brings in terms of security risks and ethical issues. It proposes an AI-enabled IoT-CPS technology for disease discovery in patients. Experimental results show that compared to existing algorithms, this technology performs more efficiently in terms of Accuracy, Precision, Recall, and F-measure.
Article
Engineering, Multidisciplinary
Manu Suvarna, Ken Shaun Yap, Wentao Yang, Jun Li, Yen Ting Ng, Xiaonan Wang
Summary: With the rise of Industry 4.0 and smart manufacturing, there is a growing belief that traditional manufacturing is transitioning towards a new paradigm focused on innovation, automation, better customer response, and intelligent systems. The concept of cyber-physical production systems (CPPS) plays a crucial role in data-driven manufacturing, decentralized manufacturing, and integrated blockchain for data security, connecting smart manufacturing aspects and transforming manufacturing towards intuition and automation.
Article
Green & Sustainable Science & Technology
Zeeshan Hussain, Adnan Akhunzada, Javed Iqbal, Iram Bibi, Abdullah Gani
Summary: The Industrial Internet of Things is driving smart manufacturing and industrial automation, but it is also a target for cyber attacks. A novel hybrid architecture utilizing deep learning is proposed to effectively combat botnet attacks in Industrial IoT. The approach is evaluated on a state-of-the-art dataset and shows promising results in terms of high detection accuracy with reasonable speed efficiency.
Article
Computer Science, Interdisciplinary Applications
Shahid Latif, Zeba Idrees, Jawad Ahmad, Lirong Zheng, Zhuo Zou
Summary: This paper presents a blockchain-based secure and trustworthy architecture for industrial IoT, utilizing lightweight private blockchain, real-time cryptographic algorithms, and highly scalable consensus mechanism.
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION
(2021)
Article
Biology
Bhukya Padma, Erukala Suresh Babu
Summary: In this study, we propose a novel, lightweight encryption method based on DNA sequences for Zigbee IoT devices with limited computational resources. By taking advantage of the randomness of DNA sequences, we generate a secure key that cannot be cracked by attackers. The encryption process, which involves substitution and transposition operations, is suitable for Zigbee devices. Additionally, we use signal-to-interference and noise ratio (SINR), congestion level, and survival factor to estimate the cluster head selection factor and group the network nodes using adaptive fuzzy c-means clustering. Experimental results show that our proposed technique outperforms other encryption algorithms in terms of energy consumption metrics such as node remaining energy level, key size, and encryption time.
Article
Computer Science, Information Systems
Zijie Ji, Phee Lep Yeoh, Gaojie Chen, Junqing Zhang, Yan Zhang, Zunwen He, Hao Yin, Yonghui Li
Summary: This article proposes a wireless key generation solution to prevent active jamming attacks in Industrial Internet of Things (IIoT) applications. The solution utilizes one-time pad (OTP) encryption and one-way self-interference (SI) for low-latency, high-security communication. Analytical comparisons and simulation results confirm the advantages of this proposed scheme.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Hardware & Architecture
M. Ramanan, Laxman Singh, A. Suresh Kumar, A. Suresh, A. Sampathkumar, Vishal Jain, Nebojsa Bacanin
Summary: Breast cancer is a significant threat to women, and this study proposes a safe data transfer solution based on blockchain technology, improving the accuracy of breast cancer detection and classification through analysis of mammogram images.
COMPUTERS & ELECTRICAL ENGINEERING
(2022)
Article
Computer Science, Information Systems
Muhammad Umer, Saima Sadiq, Hanen Karamti, Reemah M. Alhebshi, Khaled Alnowaiser, Ala' Abdulmajid Eshmawi, Houbing Song, Imran Ashraf
Summary: This paper discusses the security threats, vulnerabilities, challenges, and attacks of cyber-physical systems (CPS). It presents the architecture of CPS and elaborates on the different cyber-physical attacks and associated issues. The application of deep learning models in CPS and their performance comparison is also analyzed. Future research directions for cyber-physical security are provided.
Article
Green & Sustainable Science & Technology
Shatha Alharbi, Afraa Attiah, Daniyal Alghazzawi
Summary: The rising popularity of the Internet of Things (IoT) has brought attention to the security concerns of IoT networks, which lack intrinsic security mechanisms due to the limited capabilities of IoT devices. Research calls for the establishment of a scalable, decentralized, and adaptive defense system for IoT networks.
Article
Computer Science, Information Systems
Qian Chen, Paul Romanowich, Jorge Castillo, Krishna Chandra Roy, Gustavo Chavez, Shouhuai Xu
Summary: The article introduces a new approach for detecting vehicle cyber attacks, by utilizing human, physical, and driving behaviors to create a novel framework. Experimental results demonstrate that the framework is effective in detecting and preventing deadly crashes caused by vehicle cyber attacks.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Jairo A. Giraldo, Mohamad El Hariri, Masood Parvania
Summary: This article proposes a novel moving target defense (MTD) strategy that enhances the security of cyber-physical systems (CPSs) by replicating relevant sensory and control signals using the versatility of IoT networks. The replicated data, selected randomly, create two layers of uncertainties that reduce the ability of adversaries to launch successful cyberattacks without affecting the system's performance in normal operation. The article also develops the theoretical foundations for designing the IoT network and allocating replicas per signal for linear-time-invariant systems while calculating the fundamental limits of uncertainties introduced by the framework. Experimental implementation on a real-time water system over a WiFi network demonstrates the orchestration of layers and integrated applications in the proposed framework, significantly limiting the impact of false-data-injection attacks and decreasing adversaries' ability to learn about the physical system operation.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Qing Wang, Xiwang Dong, Jinhu Lu, Zhang Ren
Summary: This paper studies the problem of time-varying output formation tracking for directed multi-agent systems, where the leader has unknown input and each follower has nonidentical dynamics. The main objective of this paper is to construct a fully distributed controller that enables the followers to track the leader's output and realize the expected formation simultaneously. Two adaptive observers are constructed to estimate the states of the leader and followers, respectively, by exploiting neighboring information and local estimation. A fully distributed TVOFT control protocol is developed using the distributed observers and the expected time-varying formation vector, and the parameters of the controller are designed through a three-step algorithm. The TVOFT criteria for the considered closed-loop multi-agent systems are obtained based on the Lyapunov stability theory and output regulation method.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Automation & Control Systems
Guoliang Zhu, Kexin Liu, Haibo Gu, Lei Chen, Jinhu Lu
Summary: This article investigates the consensus-based formation control problem in multi-agent systems with unknown disturbances. The proposed node-based adaptive controllers eliminate the effect of disturbances and avoid continuous communications. It is shown that the formation errors tend to zero when the derivatives of disturbances belong to Script capital L2 $$ {\mathcal{L}}_2 $$ space or are bounded by a small threshold. Zeno behaviors and global information are excluded. Numerical simulations validate the effectiveness of the proposed approaches.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Computer Science, Artificial Intelligence
Chengfang Hu, Guanghui Wen, Shuai Wang, Junjie Fu, Wenwu Yu
Summary: This article proposes a new class of distributed multiagent reinforcement learning (MARL) algorithm for addressing the dynamic economic dispatch problem (DEDP) in smart grids with coupling constraints. The algorithm utilizes a quadratic function to approximate the state-action value function and solves a convex optimization problem to obtain the approximate optimal solution. Furthermore, an improved experience replay mechanism is introduced to enhance the stability of the training process. The effectiveness and robustness of the proposed MARL algorithm are verified through simulations.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Automation & Control Systems
Chengxin Xian, Yu Zhao, Zheng-Guang Wu, Guanghui Wen, Ji-An Pan
Summary: This article investigates the event-triggered distributed average tracking (ETDAT) control problems for Lipschitz-type nonlinear multiagent systems with bounded time-varying reference signals. Two types of ETDAT algorithms, static and adaptive-gain, are developed using the state-dependent gain design approach and event-triggered mechanism. The study introduces the event-triggered strategy into DAT control algorithms for the first time and explores the ETDAT problem for multiagent systems with Lipschitz nonlinearities, which is more practical for real physical systems and meets the needs of practical engineering applications.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Xiao Min, Simone Baldi, Wenwu Yu
Summary: This article investigates the finite-time distributed adaptive consensus for nonlinear uncertain multiagent systems (MASs). The achievement includes a novel error transformation to prespecify the performance and an extension of the funnel control method in a MAS setting, showing that finite-time stability can be attained without extra complexity.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Mohammadreza Radmanesh, Hossein Ghorbanzadeh, Ahmad Asgharian Rezaei, Mahdi Jalili, Xinghuo Yu
Summary: Recently, network embedding has gained attention for enhancing network computation tasks, and the objective is to represent network nodes in a low-dimensional vector space. However, the asymmetric nature of directed networks poses challenges on preserving edge directions during the embedding process. To address this issue, a novel deep asymmetric attributed network embedding model called AAGCN is proposed, which introduces two neighborhood feature aggregation schemes to preserve asymmetric proximity and similarity. AAGCN achieves superior performance compared to state-of-the-art embedding methods in tasks like network reconstruction and link prediction.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Automation & Control Systems
Bing Mao, Xiaoqun Wu, Jinhu Lu, Guanrong Chen
Summary: This article investigates the uniformly predefined-time bounded consensus of leader-following multiagent systems with unknown system nonlinearity and external disturbance. Distributed adaptive fuzzy control is used to analyze and design the system, achieving global consensus within a predefined time.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Xinli Shi, Guanghui Wen, Jinde Cao, Xinghuo Yu
Summary: In distributed optimization, algorithms need to converge quickly and have low computation cost. Boundedness of control inputs is required for practical networking agent systems. Based on the finite-time distributed average tracking (FTDAT) problem, three types of discontinuous dynamics with bounded inputs are designed for solving unconstrained and constrained DO problems. The algorithms successfully find optimal solutions and achieve consensus in finite time.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Engineering, Electrical & Electronic
Ali Moradi Amani, Miquel A. Fiol, Mahdi Jalili, Guanrong Chen, Xinghuo Yu, Lewi Stone
Summary: This article proposes an analytical metric to measure the effect of node removal on the Laplacian eigenvalues of a network. The metric is applicable to both undirected and strongly-connected directed networks, and provides a reliable approximation for the Laplacian energy of the network. Experimental results demonstrate that this metric has high precision in predicting the central nodes of the network and outperforms other comparable heuristic methods.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Automation & Control Systems
Qiang Chen, Yu Zhao, Guanghui Wen, Guoqing Shi, Xinghuo Yu
Summary: This article studies the fixed-time distributed consensus tracking and fixed-time distributed average tracking problems for double-integrator-type multiagent systems with bounded input disturbances. A practical robust fixed-time sliding-mode control method based on the time-based generator is proposed. Various observers are designed to estimate state disagreement and measure the average value of reference signals.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Peijun Wang, Guanghui Wen, Wenwu Yu, Tingwen Huang, Xinghuo Yu
Summary: Achieving zero error consensus tracking in multiagent systems with nonautonomous leaders is challenging. We propose an adaptive continuous controller to achieve this goal for Lipschitz nonlinear MASs with a nonautonomous leader and directed communication topology.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Kunrui Ze, Wei Wang, Kexin Liu, Jinhu Lu
Summary: This article presents a novel method for optimization-based obstacle avoidance and distributed regular polygon time-varying formation control for multiple unmanned aerial vehicle systems (UAVs) in clutter environment. The method involves a leader-following structure with a directed communication graph, real-time trajectory planning for the leader UAV, and an optimization-based safe trajectory and formation size online planning algorithm. The method also includes distributed smooth adaptive filters to estimate the safe trajectory and formation size, as well as a geometric tracking controller for each UAV. Experimental results demonstrate the effectiveness of the proposed method.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Automation & Control Systems
Zhi Feng, Guoqiang Hu, Xiwang Dong, Jinhu Lu
Summary: This article addresses finite-time connectivity-preserving rendezvous problems of networked uncertain Euler-Lagrange systems, where two types of time-varying leaders are investigated, and only a subset of followers can have access to the leader's trajectory. The distributed estimation and control architecture is then established to solve this problem with an emphasis on the settling-time estimation.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Engineering, Multidisciplinary
Zhi Feng, Guoqiang Hu, Xiwang Dong, Jinhu Lu
Summary: This article presents the design of adaptively distributed Nash Equilibrium (NE) seeking algorithms for heterogeneous general linear multi-agent systems in noncooperative games. The algorithms adjust the edges of the graph to deal with nonidentical dynamics and seeking NE. Global asymptotic convergence is achieved through leveraging monotone and matrix properties.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)