Article
Telecommunications
Ibrahim Elleuch, Ali Pourranjbar, Georges Kaddoum
Summary: In a multi-user wireless network, users trying to learn anti-jamming strategies may face interference, and a solution is proposed to cooperatively learn anti-jamming techniques using distributed learning algorithms. A novel distributed multi-agent reinforcement learning algorithm is introduced, where users learn each other's strategies without the need for communication, resulting in improved transmission rates and elimination of mutual interference.
IEEE COMMUNICATIONS LETTERS
(2021)
Article
Telecommunications
Bassma S. Alsulami, Chandra Bajracharya, Danda B. Rawat
Summary: This paper investigates the use of coalition game theory as a defense mechanism in wireless virtual networks to combat attacks from jammers and eavesdroppers, aiming to protect the communication privacy of legitimate users by increasing signal quality and reducing secrecy rates.
DIGITAL COMMUNICATIONS AND NETWORKS
(2021)
Article
Computer Science, Information Systems
Kai-Ju Wu, Yao-Win Peter Hong, Jang-Ping Sheu
Summary: This paper addresses the coexistence problem among multiple wireless body area networks by formulating the channel allocation problem as a graph coloring problem and proposing a distributed two-hop incomplete coloring algorithm. Simulation results show that the proposed algorithm achieves better co-channel reuse and higher throughput than existing methods.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Computer Science, Information Systems
Mohammad Reza Heidarpour, Mohammad Hossein Manshaei, Masoud Ardakani
Summary: The Internet of Things (IoT) benefits greatly from wireless sensor networks (WSNs). However, WSNs, due to their low-power nature, are susceptible to physical jamming attacks. This study focuses on WSNs with multiple gateways, where a smart jammer may attack many sensors. The proposed defense method is to develop a gateway selection and sensors' associations policy that takes the jammer into account, achieving stable and optimal results.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2023)
Article
Computer Science, Information Systems
Yizhou Yang, David Smith, Jathushan Rajasegaran, Suranga Seneviratne
Summary: Recent advances in the Internet of Things (IoT) are revolutionizing the healthcare industry by improving communication efficiency, reducing costs, and enhancing mobility. This study proposes LSTM-based neural network prediction methods for accurate and stable channel gain prediction in wireless body area networks (BANs). An incremental learning scheme is developed for the lightweight NN predictor, LiteLSTM, to operate efficiently on handheld devices while a power control based on interquartile range ensures optimal power allocation for channel prediction, outperforming existing methods in various performance metrics.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Hardware & Architecture
Abuu B. Kihero, Haji M. Furqan, M. M. Sahin, Huseyin Arslan
Summary: Security is a critical requirement for future wireless networks, and physical layer security utilizes random wireless channel features to protect communication information and processes. Future wireless networks will offer more channel features for physical layer security to meet new use case demands.
IEEE WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Jiale Wu, Chenguang Shi, Weiwei Zhang, Jianjiang Zhou
Summary: This article investigates the game theoretic power control for a distributed radar network in the presence of a smart jammer. The main objective is to minimize the total transmit power of the radar network while maintaining desirable estimation rates, considering the available power of each radar. The interactions between the radar system and the jammer are formulated as a Nash game and a Stackelberg game, respectively, and the optimal power allocation strategies for the radar system are computed, taking into account the effect of signal-dependent interference.
IEEE SYSTEMS JOURNAL
(2023)
Article
Computer Science, Hardware & Architecture
Xia Cheng, Junyang Shi, Mo Sha, Linke Guo
Summary: This paper presents a new threat to WirelessHART networks, smart selective jamming attacks, which can greatly reduce network reliability without being easily detected.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2023)
Article
Computer Science, Information Systems
Hossein Pirayesh, Huacheng Zeng
Summary: This article surveys existing jamming attacks and anti-jamming strategies in various wireless networks, aiming to provide a comprehensive understanding of the current landscape and stimulate further research efforts to secure wireless networks against jamming attacks.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2022)
Article
Engineering, Electrical & Electronic
Luca Arcangeloni, Enrico Testi, Andrea Giorgetti
Summary: Detecting reactive jammers in wireless networks is a challenge. This study proposes a novel framework using external RF sensors to detect reactive jamming. It relies on an underdetermined blind source separation method and a jamming detection based on causal inference. The framework is applied to a LoRa-based IoT system and outperforms existing methods in the presence of shadowing.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Review
Computer Science, Information Systems
D. M. G. Preethichandra, Lasitha Piyathilaka, Umer Izhar, Rohan Samarasinghe, Liyanage C. De Silva
Summary: This paper provides a comprehensive review of wireless body area network, covering architectures, network topologies, communication protocols, security requirements, threats, and authentication methods. It also includes detailed discussions on antenna types, designs, and flexible antennas used in WBAN, as well as energy harvesting technologies and power management methods. Furthermore, recent developments in wearable sensors and novel materials are reviewed, and the application areas of WBAN are discussed.
Article
Engineering, Electrical & Electronic
Liang Xiao, Siyuan Hong, Shiyu Xu, Helin Yang, Xiangyang Ji
Summary: In this paper, an intelligent reflecting surface (IRS)-aided reinforcement learning (RL) based secure WBAN transmission scheme is proposed to optimize the sensor encryption key, transmit power, and IRS phase shifts against active eavesdropping. The Dyna architecture is used to improve learning efficiency, and safe exploration is applied to avoid data leakage. Furthermore, a deep RL based WBAN transmission scheme is introduced to enhance secure transmission performance.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Computer Science, Hardware & Architecture
Weizheng Wang, Yaoqi Yang, Latif U. Khan, Dusit Niyato, Zhu Han, Mohsen Guizani
Summary: This article provides an overview of security attacks and concerns in a digital twin (DT)-enabled wireless system. It proposes a general framework for future DT-enabled wireless systems and presents two use cases to demonstrate the effectiveness of the framework.
IEEE WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Giuseppe Coviello, Gianfranco Avitabile, Antonello Florio, Claudio Talarico, Janet M. Wang-Roveda
Summary: The paper presents a Fractional Low-power time Synchronization Algorithm (FLSA) designed for Wireless Body Area Networks, utilizing the fractional-time concept from Phase-Locked Loops theory for precise timer corrections and an heuristic routine for managing radio section power consumption. Experimental results demonstrate the benefits of the proposed algorithm.
Article
Chemistry, Analytical
Nicolas Lopez-Vilos, Claudio Valencia-Cordero, Richard Demo Souza, Samuel Montejo-Sanchez
Summary: In this paper, a novel clustering-based self-healing strategy called fairness cooperation with power allocation (FCPA) is proposed to overcome jamming attacks. The strategy can detect jamming, adjust transmit power, and use relays to extend the lifetime of subnetworks, resulting in more efficient information transmission and energy efficiency compared to other strategies.
Article
Engineering, Electrical & Electronic
Liang Xiao, Hailu Zhang, Yilin Xiao, Xiaoyue Wan, Sicong Liu, Li-Chun Wang, H. Vincent Poor
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2020)
Article
Engineering, Electrical & Electronic
Xiaozhen Lu, Liang Xiao, Tangwei Xu, Yifeng Zhao, Yuliang Tang, Weihua Zhuang
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2020)
Article
Computer Science, Information Systems
Wen Bai, Yuxiao Zhang, Weiwei Huang, Yipeng Zhou, Di Wu, Gang Liu, Liang Xiao
MULTIMEDIA TOOLS AND APPLICATIONS
(2020)
Article
Engineering, Civil
Liang Xiao, Donghua Jiang, Ye Chen, Wei Su, Yuliang Tang
IEEE JOURNAL OF OCEANIC ENGINEERING
(2020)
Article
Telecommunications
Wei Su, Jincheng Tao, Yuehua Pei, Xudong You, Liang Xiao, En Cheng
Summary: The proposed algorithm utilizes reinforcement learning to continuously estimate image quality and communication performance parameters, selecting the most suitable modulation and coding method to enhance underwater image communication efficiency. Sea test results demonstrate significant improvements in sensor performance.
IEEE COMMUNICATIONS LETTERS
(2021)
Article
Computer Science, Information Systems
Yilin Xiao, Liang Xiao, Xiaozhen Lu, Hailu Zhang, Shui Yu, H. Vincent Poor
Summary: This study introduces a deep reinforcement learning model for recommendation systems, which uses differential privacy to protect user privacy and leverages deep reinforcement learning to optimize the tradeoff between privacy protection and recommendation quality. Simulation results demonstrate that this scheme enhances user privacy protection without compromising recommendation quality compared to benchmark schemes.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Liang Xiao, Yuzhen Ding, Jinhao Huang, Sicong Liu, Yuliang Tang, Huaiyu Dai
Summary: This paper proposes a reinforcement learning-based UAV anti-jamming video transmission scheme, which can improve video quality, reduce transmission latency and energy consumption, and uses deep learning to accelerate the learning process.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2021)
Article
Computer Science, Hardware & Architecture
Yilin Xiao, Liang Xiao, Zefang Lv, Guohang Niu, Yuzhen Ding, Wenyuan Xu
Summary: This article proposes a low-latency VIoT video streaming scheme based on reinforcement learning, allowing base stations to choose streaming policies based on received signal strength, buffer queue length, jamming power, and video quality, with a deep RL version for base stations with sufficient computational resources.
IEEE WIRELESS COMMUNICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Helin Yang, Jun Zhao, Zehui Xiong, Kwok-Yan Lam, Sumei Sun, Liang Xiao
Summary: The paper presents an asynchronous federated learning framework for multi-UAV-enabled networks, which allows for distributed computing and enhances federated convergence speed and accuracy through device selection strategy and A3C-based algorithm.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Minghui Min, Liang Xiao, Jiahao Ding, Hongliang Zhang, Shiyin Li, Miao Pan, Zhu Han
Summary: This paper focuses on location privacy protection in indoor 3D space and proposes a rigorous and provable measurement method called geo-indistinguishability (3D-GI). A mechanism is developed to guarantee geo-indistinguishability by considering the height dimension of location data. The discretization noise-adding mechanism under finite precision of hardware/devices is also studied. Furthermore, a truncation mechanism is proposed to limit the generated perturbed locations within a specific region.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2022)
Article
Computer Science, Information Systems
Xu Chen, Liang Xiao, Wei Feng, Ning Ge, Xianbin Wang
Summary: The proliferation of DDoS attacks in IoT poses threats to security and system performance, and collaborative packet sampling can effectively detect and block such attacks.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Proceedings Paper
Computer Science, Information Systems
Siyuan Hong, Xiaozhen Lu, Liang Xiao, Guohang Niu, Helin Yang
Summary: In this paper, a reinforcement learning based sensor encryption and power control scheme is proposed to resist active eavesdropping in wireless body area networks. The scheme significantly decreases the eavesdropping rate and transmission latency through a secure sensing data transmission game between the coordinator and the eavesdropper.
WIRELESS ALGORITHMS, SYSTEMS, AND APPLICATIONS, WASA 2021, PT II
(2021)
Article
Telecommunications
Minghui Min, Weihang Wang, Liang Xiao, Yilin Xiao, Zhu Han
Summary: This paper introduces a sensitive semantic location privacy protection scheme based on reinforcement learning and differential privacy, which optimizes perturbation policy to balance privacy and quality of service loss. In addition, a deep deterministic policy gradient-based semantic location perturbation scheme is developed and simulations demonstrate its outperformance compared to benchmark schemes.
CHINA COMMUNICATIONS
(2021)
Article
Computer Science, Theory & Methods
Liang Xiao, Xiaozhen Lu, Tangwei Xu, Weihua Zhuang, Huaiyu Dai
Summary: This paper proposes a CAN bus authentication framework that leverages physical layer features and reinforcement learning to improve authentication accuracy. A deep learning version is also introduced to enhance authentication efficiency. Experimental results confirm the improvements in authentication accuracy achieved by the proposed schemes.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2021)
Proceedings Paper
Computer Science, Hardware & Architecture
Xudong You, Zefang Lv, Yuzhen Ding, Wei Su, Liang Xiao
2020 12TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING (WCSP)
(2020)
