Article
Computer Science, Hardware & Architecture
Haijun Tan, Ning Xie, Alex X. Liu
Summary: This article discusses the physical layer security problem in distributed antenna systems, and proposes a new PLS scheme using one-bit feedback information. The scheme generates a null transmission vector and artificial noise to protect the channel state information between the communicating parties, achieving improved secrecy rate, rapid convergence, and good performance under time-varying channels.
Article
Computer Science, Information Systems
Pablo Angueira, Inaki Val, Jon Montalban, Oscar Seijo, Eneko Iradier, Pablo Sanz Fontaneda, Lorenzo Fanari, Aitor Arriola
Summary: The industrial environment imposes strict requirements on the infrastructure of communication systems. Wireless systems are a solution, but they have weaknesses in reliability and security. This paper analyzes the security challenges of radio-frequency wireless systems in industrial applications and proposes a methodology for designing protection techniques.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2022)
Review
Computer Science, Information Systems
Attique Ur Rehman, Muhammad Sajid Mahmood, Muhammad Ahsan Raza, Fahad Qaswar, Sumayh S. Aljameel, Irfan Ullah Khan, Nida Aslam
Summary: Physical layer security for wireless sensor networks is a critical issue. Challenges include data security in wireless transmission and threats to the physical security of networks. The paper surveys parameters of a security design model and discusses attacks and mitigation techniques at different layers. Additionally, it introduces applications of WSNs in various fields and proposes a solution to enhance WSN security.
Article
Automation & Control Systems
Songlin Chen, Zhibo Pang, Hong Wen, Kan Yu, Tengyue Zhang, Yueming Lu
Summary: The article proposes a scheme using channel-based machine learning to detect clone and Sybil attacks, by exploring channel responses between sensor peers for unique fingerprints, providing accurate authentication rates, and achieving success in industrial environments without manual labeling.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Telecommunications
Indrakshi Dey, Hemdutt Joshi, Nicola Marchetti
Summary: This letter addresses the issue of interference caused by superposition of multiple sensor signals in wireless sensor networks, and proposes the use of space-time spreading (STS) to minimize interference. By applying STS to sensor decisions before transmission, the performance of the transmission is significantly improved.
IEEE COMMUNICATIONS LETTERS
(2021)
Article
Computer Science, Information Systems
Yilun Sun, Guyue Li, Hongyi Luo, Yuexiu Xing, Shuping Dang, Aiqun Hu
Summary: Pseudo base stations are illegal devices that exploit security vulnerabilities of 5G communications and conduct network attacks, posing threats to the deployment of wireless access networks. Efficient methods for identifying base stations are necessary. This letter proposes a signal echoing protocol to reduce channel interference and create location-invariant radio frequency fingerprints, achieving high accuracy in base station classification.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2023)
Article
Telecommunications
R. Pradeep, R. Kanimozhi
Summary: Wireless communication technology is essential in our daily lives, but faces challenges such as secure transmission and energy efficiency. The proposed Hardware Efficient Secure Channel Coding Scheme aims to address these issues through innovative coding methods.
WIRELESS PERSONAL COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Zahra Ezzati Khatab, Abbas Mohammadi, Vahid Pourahmadi, Ali Kuhestani
Summary: This paper proposes a machine learning relay assisted authentication method for dual-hop MIMO systems. By utilizing channel characteristics for physical layer authentication and using neural networks to distinguish legitimate transmitters from attackers, the proposed method achieves an authentication accuracy of over 90%.
Article
Computer Science, Hardware & Architecture
Youhong Feng, Shihao Yan, Nan Yang, Zhen Yang, Jinhong Yuan
Summary: This article clarifies key security issues in NOMA technology, including the channel conditions for eavesdroppers to use SIC for interference cancellation, the improvement of security for strong users and the reduction of security for weak users with NOMA, and strategies to protect weak user information while allowing strong users to benefit from NOMA. The article also discusses research challenges and future work in NOMA security.
Article
Automation & Control Systems
Fei Pan, Hong Wen, Xuesong Gao, Haibo Pu, Zhibo Pang
Summary: Existing clone detection schemes for industrial wireless cyber-physical systems are either based on upper layer observations or physical layer channel state information. This article proposes a scheme that applies physical layer reputation and back propagation neural network to improve detection accuracy. The scheme accumulates physical layer reputations and inputs them to the neural network for attack detection and tracing.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Computer Science, Information Systems
Jose David Vega Sanchez, Pablo Ramirez-Espinosa, F. Javier Lopez-Martinez
Summary: The analysis of physical layer security (PLS) performance in wireless communication links with a large reflecting surface (LRS) and phase errors shows that LRS-aided communications have great potential to enhance PLS in practical wireless set-ups. The eavesdropper's link is Rayleigh distributed and independent of the legitimate link, demonstrating different scaling laws for legitimate and eavesdroppers signal-to-noise ratios with the number of reflecting elements. Additionally, even with coarse phase quantization, the performance is reasonably good, indicating promising results for PLS enhancements.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2021)
Article
Engineering, Electrical & Electronic
Ziya Gulgun, Emil Bjornson, Erik G. Larsson
Summary: This paper evaluates the uplink spectral efficiency of a single-cell massive MIMO system with distributed jammers, comparing different attack scenarios and decoding vectors. It is found that zero-forcing (ZF) decoding provides higher SE than maximum-ratio-combining (MRC), with no impact from the choice of channel estimators. The performance loss of massive MIMO is shown to be lower than SIMO systems, and power control algorithms can improve the system's sum SE.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Tong-Xing Zheng, Xin Chen, Chao Wang, Kai-Kit Wong, Jinhong Yuan
Summary: This paper investigates physical layer security for a large-scale WSN with random multiple access, and proposes a random jamming scheme to defeat eavesdroppers. Analytical models are developed to characterize transmission reliability and secrecy, and an optimization problem is formulated to maximize the sum secrecy throughput. The results show that the random jamming scheme improves secrecy throughput, and the optimal jamming probability is determined by the trade-off between secrecy and throughput.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Computer Science, Theory & Methods
Gabriele Oligeri, Savio Sciancalepore, Simone Raponi, Roberto Di Pietro
Summary: Physical-layer security is an important topic in wireless communications, and recent research has focused on using deep learning algorithms for sender authentication. Prior work has mainly focused on terrestrial wireless devices and has not considered satellite transmitters. This paper investigates the use of AI-based solutions for the authentication of Low-Earth Orbit (LEO) satellites, which present unique challenges due to their non-standard electronics and specific characteristics. The study uses a large dataset collected from an extensive measurement campaign on the IRIDIUM LEO satellites and shows that Convolutional Neural Networks (CNN) and autoencoders can be successfully used for authentication with high accuracy. However, the number of samples required and the low bandwidth of the satellite link may limit the detection of spoofing attacks under certain configuration parameters.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2023)
Article
Computer Science, Information Systems
Yanru Chen, Zhengyu Chen, Yuanyuan Zhang, Zhiyuan Luo, Yang Li, Bin Xing, Bing Guo, Liangyin Chen
Summary: Recently, there has been significant attention from researchers in using wireless channel state information (CSI) for generating encryption keys in the physical layer. This approach relies on the variability of the wireless channel, channel reciprocity, and spatial decorrelation to ensure security, making it lightweight and providing strong randomness. The proposed scheme in this article utilizes a feature fusion autoencoder (FFAEncoder) to address the high key disagreement rate (KDR) in wireless LAN MIMO systems, achieving better key generation performance than current models.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Hardware & Architecture
Fabio Palumbo, Giuseppe Aceto, Alessio Botta, Domenico Ciuonzo, Valerio Persico, Antonio Pescape
Summary: Monitoring and evaluating cloud network performance is crucial, with experiments and analysis supporting cloud customers and providers in making informed decisions. The study reveals network performance characteristics perceived by global users and provides data support for multi-cloud deployment of cloud services.
Article
Computer Science, Hardware & Architecture
Giuseppe Aceto, Domenico Ciuonzo, Antonio Montieri, Antonio Pescape
Summary: This paper proposes a novel multimodal multitask deep learning approach for traffic classification, which effectively utilizes traffic data heterogeneity while simultaneously addressing different traffic classification problems associated with different providers. EVALUATING on a public dataset of encrypted traffic, the proposed DISTILLER classifier shows improvements over other state-of-the-art deep learning architectures for encrypted traffic classification.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Domenico Ciuonzo, Pierluigi Salvo Rossi, Pramod K. Varshney
Summary: This article addresses the issue of distributed detection of a noncooperative target with a wireless sensor network, using one-bit sensor measurement quantization and investigating two quantization strategies. The proposed approaches, including Rao and locally optimum detection tests, show promising performance in simulation results.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Hardware & Architecture
Antonio Montieri, Giampaolo Bovenzi, Giuseppe Aceto, Domenico Ciuonzo, Valerio Persico, Antonio Pescape
Summary: This paper investigates the prediction of mobile-app traffic at packet-level granularity using advanced Deep Learning algorithms and compares the results with Markovian and classic Machine Learning approaches, showing improved performance. The study provides valuable insights into the variability in prediction performance among different app categories and aims to strike the best balance among performance measures.
Article
Environmental Sciences
Hossein Darvishi, Mohammad Ali Sebt, Domenico Ciuonzo, Pierluigi Salvo Rossi
Summary: This article proposes two methods based on EKF and FD processes for estimating the elevation angle of a low-angle isolated target. These methods show excellent performance in different multipath environments and low SNR conditions, making them suitable for low-peak-power radars.
Article
Computer Science, Information Systems
Alfredo Nascita, Antonio Montieri, Giuseppe Aceto, Domenico Ciuonzo, Valerio Persico, Antonio Pescape
Summary: The proliferation of mobile devices has altered the network traffic landscape, leading to new challenges in traffic classification. While Deep Learning has emerged as a solution to enhance performance compared to traditional machine learning techniques, its black-box nature hinders practical adoption in critical scenarios. Explainable Artificial Intelligence techniques have gained recent interest for providing global interpretations in contrast to sample-based ones.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Gianluca Tabella, Yuri Di Martino, Domenico Ciuonzo, Nicola Paltrinieri, Xiaodong Wang, Pierluigi Salvo Rossi
Summary: This paper addresses the distributed detection and localization of carbon dioxide release from storage tanks in an industrial context using inexpensive sensor devices. A realistic dispersion model is proposed, considering both full-precision and rate-limited setups for sensors, and fusion rules based on the dispersion model are derived. Simulations analyze the performance trends with realistic system parameters.
2022 25TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION 2022)
(2022)
Proceedings Paper
Engineering, Electrical & Electronic
Gianluca Tabella, Yuri Di Martino, Domenico Ciuonzo, Nicola Paltrinieri, Xiaodong Wang, Pierluigi Salvo Rossi
Summary: This work investigates the distributed detection of carbon dioxide release from storage tanks using inexpensive sensor devices in an industrial context. The work proposes a realistic dispersion model and fusion rules based on the dispersion model. Simulations analyze the performance trends with relevant system parameters.
2022 IEEE 12TH SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP (SAM)
(2022)
Proceedings Paper
Engineering, Electrical & Electronic
Nishanth Mudkey, Domenico Ciuonzo, Alessio Zappone, Pierluigi Salvo Rossi
Summary: This paper studies channel-aware binary-decision fusion over a shared flat-fading channel with multiple antennas, utilizing a Reconfigurable Intelligent Surface (RIS). Simulation results show that RIS adoption can improve performance even in a suboptimal case.
2022 IEEE 12TH SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP (SAM)
(2022)
Proceedings Paper
Engineering, Electrical & Electronic
Hossein Darvishi, Domenico Ciuonzo, Pierluigi Salvo Rossi
Summary: This study focuses on a modular SFDIA architecture and explores the impact of using different types of neural-network building blocks.
Proceedings Paper
Computer Science, Interdisciplinary Applications
Idio Guarino, Giampaolo Bovenzi, Davide Di Monda, Giuseppe Aceto, Domenico Ciuonzo, Antonio Pescap
Summary: Current intrusion detection techniques are incapable of dealing with the growing quantity and complexity of cyber attacks. Machine Learning techniques have been proposed for postmortem detection of network attacks, with many datasets available for training and validation purposes. This paper presents an early classification approach using CSE-CIC-IDS2018 dataset to detect malicious attacks before they can cause harm to an organization, by investigating a different set of features and analyzing the sensitivity of five classification algorithms to the number of observed packets. Results indicate that satisfactory results can be achieved with ML approaches relying on only ten packets.
2022 IEEE INTERNATIONAL SYMPOSIUM ON MEASUREMENTS & NETWORKING (M&N 2022)
(2022)
Proceedings Paper
Computer Science, Hardware & Architecture
L. Pappone, F. Cerasuolo, V Persico, D. Ciuonzo, A. Pescape, F. Esposito
Summary: This study applies Multi-task Deep Learning to predict network traffic aggregates generated by mobile video applications, showing variability in prediction performance among different video application categories, and demonstrating that using smaller time intervals can improve performance for specific traffic profiles.
2022 IFIP NETWORKING CONFERENCE (IFIP NETWORKING)
(2022)
Article
Engineering, Electrical & Electronic
Abdolreza Mohammadi, Domenico Ciuonzo, Ali Khazaee, Pierluigi Salvo Rossi
Summary: In this paper, we address the problem of distributed detection of a sparse localized phenomenon of interest (POI) in a wireless sensor network. We derive locally most powerful detectors and design local quantizati...
IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS
(2022)
Article
Engineering, Electrical & Electronic
Sami A. Aldalahmeh, Domenico Ciuonzo
Summary: This paper addresses decision fusion for distributed detection in randomly deployed clustered Wireless Sensor Networks (WSNs) operating over non-ideal multiple access channels (MACs). The proposed algorithms and fusion rules can improve the system performance by mitigating fading and considering the statistical characteristics of the received signals.
IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS
(2022)
Article
Computer Science, Information Systems
Shidrokh Goudarzi, Seyed Ahmad Soleymani, Mohammad Hossein Anisi, Domenico Ciuonzo, Nazri Kama, Salwani Abdullah, Mohammad Abdollahi Azgomi, Zenon Chaczko, Azri Azmi
Summary: This article proposes a fault-tolerant multi-level framework that integrates unmanned aerial vehicles (UAVs) and wireless sensor networks (WSN) for river level monitoring and flood prediction. A water-level prediction model based on a hybrid algorithm of Group Method Data Handling (GMDH) and Particle Swarm Optimization (PSO) is introduced and trained using real dataset. The performance of the proposed model is evaluated and compared with other models using different metrics, showing good results.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
