Pub Date : 2024-10-30DOI: 10.1109/COMST.2024.3488580
Evans Owusu;Mohamed Rahouti;Senthil Kumar Jagatheesaperumal;Kaiqi Xiong;Yufeng Xin;Lu Lu;D. Frank Hsu
Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks continue to pose significant threats to networked systems, causing disruptions that can lead to substantial financial losses. These attacks exploit vulnerabilities in network architecture to overwhelm systems, rendering them unavailable to legitimate users. The complexity and evolving nature of DoS/DDoS attacks necessitate advanced detection techniques that can operate effectively in real-time environments. This paper comprehensively examines current methodologies for online DoS/DDoS attack detection. We explore integrating sampling techniques and Change Point Detection (CPD) with Machine Learning (ML) approaches to enhance the detection and identification of DoS/DDoS activities in network traffic. We further assess the various sampling methods and their impact on the performance of online detection, considering both the efficiency and accuracy of these techniques in real-world applications. Lastly, we delve into the challenges of deploying these technologies in operational network environments, highlighting practical implications and future research directions. Our review synthesizes findings from recent studies, providing a critical analysis of existing strategies and proposing a unified framework that leverages CPD, ML, and targeted sampling to improve the resilience of networks against these disruptive cyber threats.
{"title":"Online Network DoS/DDoS Detection: Sampling, Change Point Detection, and Machine Learning Methods","authors":"Evans Owusu;Mohamed Rahouti;Senthil Kumar Jagatheesaperumal;Kaiqi Xiong;Yufeng Xin;Lu Lu;D. Frank Hsu","doi":"10.1109/COMST.2024.3488580","DOIUrl":"10.1109/COMST.2024.3488580","url":null,"abstract":"Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks continue to pose significant threats to networked systems, causing disruptions that can lead to substantial financial losses. These attacks exploit vulnerabilities in network architecture to overwhelm systems, rendering them unavailable to legitimate users. The complexity and evolving nature of DoS/DDoS attacks necessitate advanced detection techniques that can operate effectively in real-time environments. This paper comprehensively examines current methodologies for online DoS/DDoS attack detection. We explore integrating sampling techniques and Change Point Detection (CPD) with Machine Learning (ML) approaches to enhance the detection and identification of DoS/DDoS activities in network traffic. We further assess the various sampling methods and their impact on the performance of online detection, considering both the efficiency and accuracy of these techniques in real-world applications. Lastly, we delve into the challenges of deploying these technologies in operational network environments, highlighting practical implications and future research directions. Our review synthesizes findings from recent studies, providing a critical analysis of existing strategies and proposing a unified framework that leverages CPD, ML, and targeted sampling to improve the resilience of networks against these disruptive cyber threats.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 4","pages":"2543-2580"},"PeriodicalIF":34.4,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-30DOI: 10.1109/COMST.2024.3488173
Mohammad Cheraghinia;Adnan Shahid;Stijn Luchie;Gert-Jan Gordebeke;Olivier Caytan;Jaron Fontaine;Ben Van Herbruggen;Sam Lemey;Eli De Poorter
Due to their large bandwidth, relatively low cost, and robust performance, Ultra-Wideband (UWB) radio chips can be used for a wide variety of applications, including localization, communication, and radar. This article offers an exhaustive survey of recent progress in UWB radar technology. The goal of this survey is to provide a comprehensive view of the technical fundamentals and emerging trends in UWB radar. Our analysis is categorized into multiple parts. Firstly, we explore the fundamental concepts of UWB radar technology from a technology and standardization point of view. Secondly, we examine the most relevant UWB applications and use cases, such as device-free localization, activity recognition, presence detection, and vital sign monitoring, discussing each time the bandwidth requirements, processing techniques, algorithms, latest developments, relevant example papers, and trends. Next, we steer readers toward relevant datasets and available radio chipsets. Finally, we discuss ongoing challenges and potential future research avenues. As such, this overview paper is designed to be a cornerstone reference for researchers charting the course of UWB radar technology over the last decade.
{"title":"A Comprehensive Overview on UWB Radar: Applications, Standards, Signal Processing Techniques, Datasets, Radio Chips, Trends and Future Research Directions","authors":"Mohammad Cheraghinia;Adnan Shahid;Stijn Luchie;Gert-Jan Gordebeke;Olivier Caytan;Jaron Fontaine;Ben Van Herbruggen;Sam Lemey;Eli De Poorter","doi":"10.1109/COMST.2024.3488173","DOIUrl":"10.1109/COMST.2024.3488173","url":null,"abstract":"Due to their large bandwidth, relatively low cost, and robust performance, Ultra-Wideband (UWB) radio chips can be used for a wide variety of applications, including localization, communication, and radar. This article offers an exhaustive survey of recent progress in UWB radar technology. The goal of this survey is to provide a comprehensive view of the technical fundamentals and emerging trends in UWB radar. Our analysis is categorized into multiple parts. Firstly, we explore the fundamental concepts of UWB radar technology from a technology and standardization point of view. Secondly, we examine the most relevant UWB applications and use cases, such as device-free localization, activity recognition, presence detection, and vital sign monitoring, discussing each time the bandwidth requirements, processing techniques, algorithms, latest developments, relevant example papers, and trends. Next, we steer readers toward relevant datasets and available radio chipsets. Finally, we discuss ongoing challenges and potential future research avenues. As such, this overview paper is designed to be a cornerstone reference for researchers charting the course of UWB radar technology over the last decade.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 4","pages":"2283-2324"},"PeriodicalIF":34.4,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-28DOI: 10.1109/COMST.2024.3487112
Majid H. Khoshafa;Omar Maraqa;Jules M. Moualeu;Sylvester Aboagye;Telex M. N. Ngatched;Mohamed H. Ahmed;Yasser Gadallah;Marco Di Renzo
Security and latency are crucial aspects in the design of future wireless networks. Physical layer security (PLS) has received a growing interest from the research community in recent years for its ability to safeguard data confidentiality without relying on key distribution or encryption/decryption, and for its latency advantage over bit-level cryptographic techniques. However, the evolution towards the fifth generation wireless technology and beyond poses new security challenges that must be addressed in order to fulfill the unprecedented performance requirements of future wireless communications networks. Among the potential key-enabling technologies, reconfigurable intelligent surface (RIS) has attracted extensive attention due to its ability to proactively and intelligently reconfigure the wireless propagation environment to combat dynamic channel impairments. Consequently, the RIS technology can be adopted to improve the information-theoretic security of both radio frequency (RF) and optical wireless communications (OWC) systems. It is worth noting that the configuration of RIS in RF communications is different from that in optical systems at many levels (e.g., RIS materials, signal characteristics, and functionalities). This survey article provides a comprehensive overview of the information-theoretic security of RIS-based RF and optical systems. The article first discusses the fundamental concepts of PLS and RIS technologies, followed by their combination in both RF and OWC systems. Subsequently, some optimization techniques are presented in the context of the underlying system model, followed by an assessment of the impact of RIS-assisted PLS through a comprehensive performance analysis. Given that the computational complexity of future communications systems that adopt RIS-assisted PLS is likely to increase rapidly as the number of interactions between the users and infrastructure grows, machine learning (ML) is seen as a promising approach to address this complexity issue while sustaining or improving the network performance. A discussion of recent research studies on RIS-assisted PLS-based systems embedded with ML is presented. Furthermore, some important open research challenges are proposed and discussed to provide insightful future research directions, with the aim of moving a step closer towards the development and implementation of the forthcoming sixth-generation (6G) wireless technology.
{"title":"RIS-Assisted Physical Layer Security in Emerging RF and Optical Wireless Communications Systems: A Comprehensive Survey","authors":"Majid H. Khoshafa;Omar Maraqa;Jules M. Moualeu;Sylvester Aboagye;Telex M. N. Ngatched;Mohamed H. Ahmed;Yasser Gadallah;Marco Di Renzo","doi":"10.1109/COMST.2024.3487112","DOIUrl":"10.1109/COMST.2024.3487112","url":null,"abstract":"Security and latency are crucial aspects in the design of future wireless networks. Physical layer security (PLS) has received a growing interest from the research community in recent years for its ability to safeguard data confidentiality without relying on key distribution or encryption/decryption, and for its latency advantage over bit-level cryptographic techniques. However, the evolution towards the fifth generation wireless technology and beyond poses new security challenges that must be addressed in order to fulfill the unprecedented performance requirements of future wireless communications networks. Among the potential key-enabling technologies, reconfigurable intelligent surface (RIS) has attracted extensive attention due to its ability to proactively and intelligently reconfigure the wireless propagation environment to combat dynamic channel impairments. Consequently, the RIS technology can be adopted to improve the information-theoretic security of both radio frequency (RF) and optical wireless communications (OWC) systems. It is worth noting that the configuration of RIS in RF communications is different from that in optical systems at many levels (e.g., RIS materials, signal characteristics, and functionalities). This survey article provides a comprehensive overview of the information-theoretic security of RIS-based RF and optical systems. The article first discusses the fundamental concepts of PLS and RIS technologies, followed by their combination in both RF and OWC systems. Subsequently, some optimization techniques are presented in the context of the underlying system model, followed by an assessment of the impact of RIS-assisted PLS through a comprehensive performance analysis. Given that the computational complexity of future communications systems that adopt RIS-assisted PLS is likely to increase rapidly as the number of interactions between the users and infrastructure grows, machine learning (ML) is seen as a promising approach to address this complexity issue while sustaining or improving the network performance. A discussion of recent research studies on RIS-assisted PLS-based systems embedded with ML is presented. Furthermore, some important open research challenges are proposed and discussed to provide insightful future research directions, with the aim of moving a step closer towards the development and implementation of the forthcoming sixth-generation (6G) wireless technology.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 4","pages":"2156-2203"},"PeriodicalIF":34.4,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142536825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-28DOI: 10.1109/COMST.2024.3486690
Mostafa M. Fouda;Zubair Md Fadlullah;Mohamed I. Ibrahem;Nei Kato
With the proliferation of Beyond 5G (B5G) communication systems and heterogeneous networks, mobile broadband users are generating massive volumes of data that undergo fast processing and computing to obtain actionable insights. While analyzing this huge amount of data typically involves machine and deep learning-based data-driven Artificial Intelligence (AI) models, a key challenge arises in terms of providing privacy assurances for user-generated data. Even though data-driven techniques have been widely utilized for network traffic analysis and other network management tasks, researchers have also identified that applying AI techniques may often lead to severe privacy concerns. Therefore, the concept of privacy-preserving data-driven learning models has recently emerged as a hot area of research to facilitate model training on large-scale datasets while guaranteeing privacy along with the security of the data. In this paper, we first demonstrate the research gap in this domain, followed by a tutorial-oriented review of data-driven models, which can be potentially mapped to privacy-preserving techniques. Then, we provide preliminaries of a number of privacy-preserving techniques (e.g., differential privacy, functional encryption, Homomorphic encryption, secure multi-party computation, and federated learning) that can be potentially adopted for emerging communication networks. The provided preliminaries enable us to showcase the subset of data-driven privacy-preserving models, which are gaining traction in emerging communication network systems. We provide a number of relevant networking use cases, ranging from the B5G core and Radio Access Networks (RANs) to semantic communications, adopting privacy-preserving data-driven models. Based on the lessons learned from the pertinent use cases, we also identify several open research challenges and hint toward possible solutions.
{"title":"Privacy-Preserving Data-Driven Learning Models for Emerging Communication Networks: A Comprehensive Survey","authors":"Mostafa M. Fouda;Zubair Md Fadlullah;Mohamed I. Ibrahem;Nei Kato","doi":"10.1109/COMST.2024.3486690","DOIUrl":"10.1109/COMST.2024.3486690","url":null,"abstract":"With the proliferation of Beyond 5G (B5G) communication systems and heterogeneous networks, mobile broadband users are generating massive volumes of data that undergo fast processing and computing to obtain actionable insights. While analyzing this huge amount of data typically involves machine and deep learning-based data-driven Artificial Intelligence (AI) models, a key challenge arises in terms of providing privacy assurances for user-generated data. Even though data-driven techniques have been widely utilized for network traffic analysis and other network management tasks, researchers have also identified that applying AI techniques may often lead to severe privacy concerns. Therefore, the concept of privacy-preserving data-driven learning models has recently emerged as a hot area of research to facilitate model training on large-scale datasets while guaranteeing privacy along with the security of the data. In this paper, we first demonstrate the research gap in this domain, followed by a tutorial-oriented review of data-driven models, which can be potentially mapped to privacy-preserving techniques. Then, we provide preliminaries of a number of privacy-preserving techniques (e.g., differential privacy, functional encryption, Homomorphic encryption, secure multi-party computation, and federated learning) that can be potentially adopted for emerging communication networks. The provided preliminaries enable us to showcase the subset of data-driven privacy-preserving models, which are gaining traction in emerging communication network systems. We provide a number of relevant networking use cases, ranging from the B5G core and Radio Access Networks (RANs) to semantic communications, adopting privacy-preserving data-driven models. Based on the lessons learned from the pertinent use cases, we also identify several open research challenges and hint toward possible solutions.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 4","pages":"2505-2542"},"PeriodicalIF":34.4,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142536857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-28DOI: 10.1109/COMST.2024.3487472
Dilara Aktas;Beyza E. Ortlek;Meltem Civas;Elham Baradari;Ahmet B. Kilic;Fatih E. Bilgen;Ayse S. Okcu;Melanie Whitfield;Oktay Cetinkaya;Ozgur B. Akan
Humankind mimics the processes and strategies that nature has perfected and uses them as a model to address its problems. This has led to a new communication technology, molecular communication (MC), using molecules to encode, transmit, and receive information. Despite extensive research, an innate MC method found abundantly in nature-olfactory or odor communication-has not been thoroughly studied using information and communication technologies (ICT). Existing studies focus on digitizing this sense and developing actuators without examining odor-based information coding and MC principles, significantly limiting its application potential. Hence, cross-disciplinary research is needed to uncover the fundamentals of this unconventional communication modality from an ICT perspective. The ways of natural odor MC in nature need to be anatomized and engineered for end-to-end communication among humans and human-made things to enable several multi-sense augmented reality technologies reinforced with olfactory senses for novel applications and solutions in the Internet of Everything (IoE). This paper introduces odor-based molecular communication (OMC) and thoroughly examines olfactory systems, exploring odor communication in nature, including odor information, channels, reception, spatial perception, and cognitive functions. Additionally, a comprehensive comparison of various communication systems sets the foundation for further investigation. By highlighting OMC’s unique characteristics, advantages, and potential applications, this paper lays the groundwork for modeling end-to-end OMC channels, designing OMC transmitters and receivers, and developing innovative OMC techniques.
{"title":"Odor-Based Molecular Communications: State-of-the-Art, Vision, Challenges, and Frontier Directions","authors":"Dilara Aktas;Beyza E. Ortlek;Meltem Civas;Elham Baradari;Ahmet B. Kilic;Fatih E. Bilgen;Ayse S. Okcu;Melanie Whitfield;Oktay Cetinkaya;Ozgur B. Akan","doi":"10.1109/COMST.2024.3487472","DOIUrl":"10.1109/COMST.2024.3487472","url":null,"abstract":"Humankind mimics the processes and strategies that nature has perfected and uses them as a model to address its problems. This has led to a new communication technology, molecular communication (MC), using molecules to encode, transmit, and receive information. Despite extensive research, an innate MC method found abundantly in nature-olfactory or odor communication-has not been thoroughly studied using information and communication technologies (ICT). Existing studies focus on digitizing this sense and developing actuators without examining odor-based information coding and MC principles, significantly limiting its application potential. Hence, cross-disciplinary research is needed to uncover the fundamentals of this unconventional communication modality from an ICT perspective. The ways of natural odor MC in nature need to be anatomized and engineered for end-to-end communication among humans and human-made things to enable several multi-sense augmented reality technologies reinforced with olfactory senses for novel applications and solutions in the Internet of Everything (IoE). This paper introduces odor-based molecular communication (OMC) and thoroughly examines olfactory systems, exploring odor communication in nature, including odor information, channels, reception, spatial perception, and cognitive functions. Additionally, a comprehensive comparison of various communication systems sets the foundation for further investigation. By highlighting OMC’s unique characteristics, advantages, and potential applications, this paper lays the groundwork for modeling end-to-end OMC channels, designing OMC transmitters and receivers, and developing innovative OMC techniques.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 4","pages":"2658-2692"},"PeriodicalIF":34.4,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142536802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wireless Charger Network (WCN) emerges as a promising networking paradigm, employing wireless chargers with Wireless Power Transfer (WPT) technology to provide long-term and sustainable energy supply for future networks. Although extensive research has been conducted in this area over the last decade, there is currently no comprehensive survey to compile the latest literature and provide insights into future research directions. To fill this gap, our survey explores the recent developments in the active research area of WCNs. This paper starts by providing a framework of WCNs in detail, covering aspects of network architecture, various charging models, network design issues, and typical applications of WCNs. Then, we give an overview of charger deployment schemes, focusing on omnidirectional, directional, non-radiative, and heterogeneous charger deployments. We also provide an overview of charging scheduling schemes, encompassing power control, time allocation, energy beamforming, and multi-resource scheduling. Moreover, we explore communication optimization schemes, including Medium Access Control (MAC) protocols, routing protocols, broadcast transmission, and data collection. Finally, we highlight some future research directions and present corresponding open issues to advance the research on WCNs.
无线充电器网络（Wireless Charger Network， WCN）是一种极具发展前景的网络模式，它采用无线充电器和无线电力传输（Wireless Power Transfer， WPT）技术，为未来网络提供长期、可持续的能源供应。虽然在过去的十年中在这一领域进行了广泛的研究，但目前还没有全面的调查来汇编最新的文献并为未来的研究方向提供见解。为了填补这一空白，我们的调查探讨了WCNs活跃研究领域的最新发展。本文首先详细介绍了无线网络网络的框架，包括网络架构、各种收费模式、网络设计问题以及无线网络网络的典型应用。然后，我们概述了充电器部署方案，重点是全向，定向，非辐射和异构充电器部署。我们还概述了充电调度方案，包括功率控制、时间分配、能量波束形成和多资源调度。此外，我们还探讨了通信优化方案，包括介质访问控制（MAC）协议、路由协议、广播传输和数据收集。最后，对未来的研究方向进行了展望，并提出了相应的开放性问题，以促进WCNs的研究。
{"title":"Understanding Wireless Charger Networks: Concepts, Current Research, and Future Directions","authors":"Meixuan Ren;Haipeng Dai;Tang Liu;Xianjun Deng;Wanchun Dou;Yuanyuan Yang;Guihai Chen","doi":"10.1109/COMST.2024.3486820","DOIUrl":"10.1109/COMST.2024.3486820","url":null,"abstract":"Wireless Charger Network (WCN) emerges as a promising networking paradigm, employing wireless chargers with Wireless Power Transfer (WPT) technology to provide long-term and sustainable energy supply for future networks. Although extensive research has been conducted in this area over the last decade, there is currently no comprehensive survey to compile the latest literature and provide insights into future research directions. To fill this gap, our survey explores the recent developments in the active research area of WCNs. This paper starts by providing a framework of WCNs in detail, covering aspects of network architecture, various charging models, network design issues, and typical applications of WCNs. Then, we give an overview of charger deployment schemes, focusing on omnidirectional, directional, non-radiative, and heterogeneous charger deployments. We also provide an overview of charging scheduling schemes, encompassing power control, time allocation, energy beamforming, and multi-resource scheduling. Moreover, we explore communication optimization schemes, including Medium Access Control (MAC) protocols, routing protocols, broadcast transmission, and data collection. Finally, we highlight some future research directions and present corresponding open issues to advance the research on WCNs.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 4","pages":"2247-2282"},"PeriodicalIF":34.4,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142536791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-28DOI: 10.1109/COMST.2024.3487068
Armed Tusha;Hüseyin Arslan
Interference represents one of the most common barriers for the wireless communications society to bring the fully connected world to life, where everybody and everything is connected at any time, aiming to support a wide range of services and applications with increasing demand in terms of data rate with a higher degree of reliability and security, while keeping an affordable overall system capacity, complexity, and latency. Essentially, interference clearly explains the primitive nature of the wireless communications systems, where there is always an unwanted physical signal that disrupts the communication link, occurring from the physical layer (PHY) architecture of transmission signal, its interaction with the wireless channel and transceiver architecture in particular. Therefore, in past wireless technologies, waveform design along with wireless channel impairments and handset architecture define the main sources of interference, leading to inter-symbol interference (ISI), inter-carrier interference (ICI) and co-channel interference (CCI) types. In this line, recent advances in wireless technologies have revealed unprecedented interference types including inter-numerology interference (INI), inter-antenna interference (IAI), inter-waveform interference (IWI), cross-link interference (CLI) and inter-Doppler interference (IDI), while additional unique interference types are expected in near future. Consequently, a broader view of the interference has become a crucial need in order to avoid and relax its impact towards beyond 5G radio access technologies. Despite the extensive research in the literature performed by academia and industry, to the best of the authors’ knowledge, there is no work that provides a comprehensive taxonomy framework of interference sources and types, and a review of management techniques from the perspective of the PHY layer. This work aims to fill this gap in the literature. With this notation, in this survey, we propose an intuitive, generic, and expandable framework that categorizes the interference sources and their corresponding management solutions. In particular, we split the interference sources into two main groups by taking into account the user of interest such as self-user-interference (SUI) and other-user-interference (OUI), which we further classify considering the user’s intention about the presence of interference named intentional SUI (I-SUI), unintentional SUI (U-SUI), intentional OUI (I-OUI), and unintentional OUI (U-OUI). In line with this, we offer a classification of the interference management techniques regarding the source of interference. Lastly, the survey presents open research perspectives for beyond 5G wireless systems and concluding remarks.
{"title":"Interference Burden in Wireless Communications: A Comprehensive Survey From PHY Layer Perspective","authors":"Armed Tusha;Hüseyin Arslan","doi":"10.1109/COMST.2024.3487068","DOIUrl":"10.1109/COMST.2024.3487068","url":null,"abstract":"Interference represents one of the most common barriers for the wireless communications society to bring the fully connected world to life, where everybody and everything is connected at any time, aiming to support a wide range of services and applications with increasing demand in terms of data rate with a higher degree of reliability and security, while keeping an affordable overall system capacity, complexity, and latency. Essentially, interference clearly explains the primitive nature of the wireless communications systems, where there is always an unwanted physical signal that disrupts the communication link, occurring from the physical layer (PHY) architecture of transmission signal, its interaction with the wireless channel and transceiver architecture in particular. Therefore, in past wireless technologies, waveform design along with wireless channel impairments and handset architecture define the main sources of interference, leading to inter-symbol interference (ISI), inter-carrier interference (ICI) and co-channel interference (CCI) types. In this line, recent advances in wireless technologies have revealed unprecedented interference types including inter-numerology interference (INI), inter-antenna interference (IAI), inter-waveform interference (IWI), cross-link interference (CLI) and inter-Doppler interference (IDI), while additional unique interference types are expected in near future. Consequently, a broader view of the interference has become a crucial need in order to avoid and relax its impact towards beyond 5G radio access technologies. Despite the extensive research in the literature performed by academia and industry, to the best of the authors’ knowledge, there is no work that provides a comprehensive taxonomy framework of interference sources and types, and a review of management techniques from the perspective of the PHY layer. This work aims to fill this gap in the literature. With this notation, in this survey, we propose an intuitive, generic, and expandable framework that categorizes the interference sources and their corresponding management solutions. In particular, we split the interference sources into two main groups by taking into account the user of interest such as self-user-interference (SUI) and other-user-interference (OUI), which we further classify considering the user’s intention about the presence of interference named intentional SUI (I-SUI), unintentional SUI (U-SUI), intentional OUI (I-OUI), and unintentional OUI (U-OUI). In line with this, we offer a classification of the interference management techniques regarding the source of interference. Lastly, the survey presents open research perspectives for beyond 5G wireless systems and concluding remarks.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 4","pages":"2204-2246"},"PeriodicalIF":34.4,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142536826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Modern cars’ complexity and increased reliance on electronic components have made them a prime target for attackers. In particular, the in-vehicle communication system is one of the major attack surfaces, with the Controller Area Network (CAN) being the most used protocol. CAN connects electronic components with each other, allowing them to communicate and carry out control functions, as well as managing the vehicle state. However, these components, called Electronic Control Units (ECUs), can also be exploited for malicious purposes. Indeed, since the CAN bus was not designed with security features, attackers can exploit its vulnerabilities to compromise ECUs and corrupt the communication, allowing for remote vehicle control, disabling breaks, and engine shutdowns, causing significant safety threats. In response to the absence of standardized authentication protocols within the automotive domain, researchers propose diverse solutions, each with unique strengths and vulnerabilities. However, the continuous influx of new protocols and potential oversights in meeting security requirements and essential operational features further complicate the implementability of these protocols. This paper comprehensively reviews and compares the 15 most prominent authentication protocols for the CAN bus. Our analysis emphasizes their strengths and weaknesses, evaluating their alignment with critical security requirements for automotive authentication. Additionally, we evaluate protocols based on essential operational criteria that contribute to ease of implementation in predefined infrastructures, enhancing overall reliability and reducing the probability of successful attacks. Our study reveals a prevalent focus on defending against external attackers in existing protocols, exposing vulnerabilities to internal threats. Notably, authentication protocols employing hash chains, Mixed Message Authentication Codes, and asymmetric encryption techniques emerge as the most effective approaches. Through our comparative study, we classify the considered protocols based on their security attributes and suitability for implementation, providing valuable insights for future developments in the field.
{"title":"A Survey and Comparative Analysis of Security Properties of CAN Authentication Protocols","authors":"Alessandro Lotto;Francesco Marchiori;Alessandro Brighente;Mauro Conti","doi":"10.1109/COMST.2024.3486367","DOIUrl":"10.1109/COMST.2024.3486367","url":null,"abstract":"Modern cars’ complexity and increased reliance on electronic components have made them a prime target for attackers. In particular, the in-vehicle communication system is one of the major attack surfaces, with the Controller Area Network (CAN) being the most used protocol. CAN connects electronic components with each other, allowing them to communicate and carry out control functions, as well as managing the vehicle state. However, these components, called Electronic Control Units (ECUs), can also be exploited for malicious purposes. Indeed, since the CAN bus was not designed with security features, attackers can exploit its vulnerabilities to compromise ECUs and corrupt the communication, allowing for remote vehicle control, disabling breaks, and engine shutdowns, causing significant safety threats. In response to the absence of standardized authentication protocols within the automotive domain, researchers propose diverse solutions, each with unique strengths and vulnerabilities. However, the continuous influx of new protocols and potential oversights in meeting security requirements and essential operational features further complicate the implementability of these protocols. This paper comprehensively reviews and compares the 15 most prominent authentication protocols for the CAN bus. Our analysis emphasizes their strengths and weaknesses, evaluating their alignment with critical security requirements for automotive authentication. Additionally, we evaluate protocols based on essential operational criteria that contribute to ease of implementation in predefined infrastructures, enhancing overall reliability and reducing the probability of successful attacks. Our study reveals a prevalent focus on defending against external attackers in existing protocols, exposing vulnerabilities to internal threats. Notably, authentication protocols employing hash chains, Mixed Message Authentication Codes, and asymmetric encryption techniques emerge as the most effective approaches. Through our comparative study, we classify the considered protocols based on their security attributes and suitability for implementation, providing valuable insights for future developments in the field.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 4","pages":"2470-2504"},"PeriodicalIF":34.4,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10735339","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142490474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-25DOI: 10.1109/COMST.2024.3486618
Kouros Zanbouri;Md. Noor-A-Rahim;Jobish John;Cormac J. Sreenan;H. Vincent Poor;Dirk Pesch
Time-sensitive networking (TSN) is expected to be a key component of critical machine-type communication networks in areas such as Industry 4.0, robotics and autonomous vehicles. With rising mobility requirements in industrial applications and the prevalence of wireless networks, wireless network integration into TSN is becoming increasingly important. This survey article presents a comprehensive review of the current literature on wireless TSN, including an overview of the architecture of a wireless TSN network and an examination of the various wireless technologies and protocols that can be or are used in such networks. In addition, the article discusses industrial applications of wireless TSN, among them industrial automation, robotics, and autonomous vehicles. The article concludes by summarizing the challenges and open issues related to the integration of TSN into wireless networks, and by offering suggestions for future research directions.
{"title":"A Comprehensive Survey of Wireless Time-Sensitive Networking (TSN): Architecture, Technologies, Applications, and Open Issues","authors":"Kouros Zanbouri;Md. Noor-A-Rahim;Jobish John;Cormac J. Sreenan;H. Vincent Poor;Dirk Pesch","doi":"10.1109/COMST.2024.3486618","DOIUrl":"10.1109/COMST.2024.3486618","url":null,"abstract":"Time-sensitive networking (TSN) is expected to be a key component of critical machine-type communication networks in areas such as Industry 4.0, robotics and autonomous vehicles. With rising mobility requirements in industrial applications and the prevalence of wireless networks, wireless network integration into TSN is becoming increasingly important. This survey article presents a comprehensive review of the current literature on wireless TSN, including an overview of the architecture of a wireless TSN network and an examination of the various wireless technologies and protocols that can be or are used in such networks. In addition, the article discusses industrial applications of wireless TSN, among them industrial automation, robotics, and autonomous vehicles. The article concludes by summarizing the challenges and open issues related to the integration of TSN into wireless networks, and by offering suggestions for future research directions.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 4","pages":"2129-2155"},"PeriodicalIF":34.4,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10735349","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142490472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Due to the inherently open and shared nature of the wireless channels, wireless communication networks are vulnerable to jamming attacks, and effective anti-jamming measures are of utmost importance to realize reliable communications. Game theory and reinforcement learning (RL) are powerful mathematical tools in anti-jamming field. This article investigates the anti-jamming problem from the perspective of game theory and RL. First, different anti-jamming domains and anti-jamming strategies are discussed, and technological challenges are globally analyzed from different perspectives. Second, an in-depth systematic and comprehensive survey of each kind of anti-jamming solutions (i.e., game theory and RL) is presented. To be specific, some game models are discussed for game theory based solutions, including Bayesian anti-jamming game, Stackelberg anti-jamming game, stochastic anti-jamming game, zero-sum anti-jamming game, graphical/hypergraphical anti-jamming game, etc. For RL-based anti-jamming solutions, different kinds of RL are given, including Q-learning, multi-armed bandit, deep RL and transfer RL. Third, the strengths and limitations are analyzed for each type of anti-jamming solutions. Finally, we discuss the deep integration of the game theory and RL in solving anti-jamming problems, and a few future research directions are illustrated.
{"title":"Game Theory and Reinforcement Learning for Anti-Jamming Defense in Wireless Communications: Current Research, Challenges, and Solutions","authors":"Luliang Jia;Nan Qi;Zhe Su;Feihuang Chu;Shengliang Fang;Kai-Kit Wong;Chan-Byoung Chae","doi":"10.1109/COMST.2024.3482973","DOIUrl":"10.1109/COMST.2024.3482973","url":null,"abstract":"Due to the inherently open and shared nature of the wireless channels, wireless communication networks are vulnerable to jamming attacks, and effective anti-jamming measures are of utmost importance to realize reliable communications. Game theory and reinforcement learning (RL) are powerful mathematical tools in anti-jamming field. This article investigates the anti-jamming problem from the perspective of game theory and RL. First, different anti-jamming domains and anti-jamming strategies are discussed, and technological challenges are globally analyzed from different perspectives. Second, an in-depth systematic and comprehensive survey of each kind of anti-jamming solutions (i.e., game theory and RL) is presented. To be specific, some game models are discussed for game theory based solutions, including Bayesian anti-jamming game, Stackelberg anti-jamming game, stochastic anti-jamming game, zero-sum anti-jamming game, graphical/hypergraphical anti-jamming game, etc. For RL-based anti-jamming solutions, different kinds of RL are given, including Q-learning, multi-armed bandit, deep RL and transfer RL. Third, the strengths and limitations are analyzed for each type of anti-jamming solutions. Finally, we discuss the deep integration of the game theory and RL in solving anti-jamming problems, and a few future research directions are illustrated.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 3","pages":"1798-1838"},"PeriodicalIF":34.4,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142489681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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