IEEE Transactions on Cognitive Communications and Networking最新文献_第3页

Real-Time Monitoring and Mitigation of SDoS Attacks Using the SDN and New Metrics 利用 SDN 和新指标实时监控和缓解 SDoS 攻击

IF 8.6 1区计算机科学

IEEE Transactions on Cognitive Communications and Networking Pub Date : 2023-08-18 DOI: 10.1109/TCCN.2023.3306358

Dan Tang;Siyuan Wang;Siqi Zhang;Zheng Qin;Wei Liang;Sheng Xiao

{"title":"Real-Time Monitoring and Mitigation of SDoS Attacks Using the SDN and New Metrics","authors":"Dan Tang;Siyuan Wang;Siqi Zhang;Zheng Qin;Wei Liang;Sheng Xiao","doi":"10.1109/TCCN.2023.3306358","DOIUrl":"10.1109/TCCN.2023.3306358","url":null,"abstract":"Slow-rate denial-of-service (SDoS) attacks are a type of denial-of-service (DoS) attacks with a low attack rate. They have a flash-crowd nature and can be well concealed in legitimate traffic, so it is difficult to identify them by anti-DoS mechanisms. Existing solutions have drawbacks such as difficult deployment, poor real-time performance, and poor scalability. We propose a scheme for real-time monitoring and mitigation of SDoS attacks on the basis of a software-defined network (SDN) and new traffic metrics. The new traffic metrics are the coefficient of fluctuation (CoF) and pulse period coefficient (PPC), which can help us identify SDoS attacks in the network and locate the attackers quickly and accurately. Based on the two metrics, the scheme uses a Gaussian mixture model (GMM) to predict and cluster network traffic and obtain attacker IPs. The mitigation module installs flow rules to discard attacking flows. With blacklisting and weighted IPs, the mitigation module reduces the probability of dropping legitimate flows in case of false positives. Experiments show that our scheme is inexpensive to deploy and can identify attacks and locate attackers quickly and accurately. The mitigation strategy can mitigate SDoS attacks within 4 to 6 seconds with high probability.","PeriodicalId":13069,"journal":{"name":"IEEE Transactions on Cognitive Communications and Networking","volume":"9 6","pages":"1721-1733"},"PeriodicalIF":8.6,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62525582","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}

引用次数: 0

On the Performance of Cooperative NOMA Downlink: A RIS-Aided D2D Perspective 论合作 NOMA 下行链路的性能：RIS 辅助 D2D 视角

IF 8.6 1区计算机科学

IEEE Transactions on Cognitive Communications and Networking Pub Date : 2023-08-18 DOI: 10.1109/TCCN.2023.3306354

Xiaohui Gu;Guoan Zhang;Biting Zhuo;Wei Duan;Jue Wang;Miaowen Wen;Pin-Han Ho

{"title":"On the Performance of Cooperative NOMA Downlink: A RIS-Aided D2D Perspective","authors":"Xiaohui Gu;Guoan Zhang;Biting Zhuo;Wei Duan;Jue Wang;Miaowen Wen;Pin-Han Ho","doi":"10.1109/TCCN.2023.3306354","DOIUrl":"10.1109/TCCN.2023.3306354","url":null,"abstract":"For future wireless communication networks to be highly efficient with both spectrum and energy, reconfigurable intelligent surface (RIS) has emerged as a practical technology. In this paper, we investigate an RIS-aided cooperative non-orthogonal multiple access (C-NOMA) system serving two power-domain users, where a near user as a decode-and-forward (DF) half-duplex (HD) relay performs device-to-device (D2D) communications for a far user. RIS is configured in time division multiple access (TDMA), which is on the one hand used to support the communication between BS and near user in the direct transmission phase, and on the other hand, for enhancing D2D communications between the two users. In an effort of evaluating the network performance, we derive closed-form expressions of achievable rates, outage probabilities (OPs), and the corresponding asymptotic OPs. The numerical results demonstrate the achievable performance improvements of the proposed cooperative RIS-NOMA system in comparison to that of the orthogonal multiple access (OMA) counterpart. In addition, the proposed cooperative RIS-NOMA system achieves various levels of diversity gains by incorporating different numbers of RIS elements.","PeriodicalId":13069,"journal":{"name":"IEEE Transactions on Cognitive Communications and Networking","volume":"9 6","pages":"1610-1624"},"PeriodicalIF":8.6,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62525544","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}

引用次数: 0

Intelligent Anti-Jamming Decision With Continuous Action and State in Bivariate Frequency Agility Communication System 双变量频率敏捷通信系统中的连续行动和状态智能抗干扰决策

IF 8.6 1区计算机科学

IEEE Transactions on Cognitive Communications and Networking Pub Date : 2023-08-18 DOI: 10.1109/TCCN.2023.3306363

Yupei Zhang;Zhijin Zhao;Shilian Zheng;Fangfang Qiang

{"title":"Intelligent Anti-Jamming Decision With Continuous Action and State in Bivariate Frequency Agility Communication System","authors":"Yupei Zhang;Zhijin Zhao;Shilian Zheng;Fangfang Qiang","doi":"10.1109/TCCN.2023.3306363","DOIUrl":"10.1109/TCCN.2023.3306363","url":null,"abstract":"The conventional frequency hopping (FH) system is susceptible to malicious jamming due to the prearranged hopping frequency table. In this paper, we develop a bivariate frequency agility (BFA) communication system to improve the anti-jamming capability by assigning time-varying characteristics to the communication parameters such as fixed frequency interval and hopping rate in conventional FH. Our goal is to find the optimal frequency interval and hopping rate strategy in jamming environment to maximize the signal-to-noise ratio (SINR). We formulate the parameter decision problem as a Markov decision process (MDP). Then, we propose a deep deterministic policy gradient (DDPG) based algorithm for frequency interval selection and hopping rate setting. In addition, to overcome the shortcomings of DDPG, which is prone to fall into local optimum and unstable convergence, an improved deep deterministic policy gradient algorithm with a weighted dual-prioritized experience replay and periodically updated learning rate (IDDPG) is proposed. In IDDPG, on the one hand, the model is trained by replaying more experiences with high immediate reward and large temporal difference error (TD error) to make it more accurate. On the other hand, the learning rate is periodically decayed so that the update rate of the network model varies periodically, resulting in a richer and more diverse exploration. The simulation results under different electromagnetic jamming environment indicates that the anti-jamming performance of the proposed two algorithms outperforms that of the PPER-DQN algorithm and the RFH algorithm.","PeriodicalId":13069,"journal":{"name":"IEEE Transactions on Cognitive Communications and Networking","volume":"9 6","pages":"1579-1595"},"PeriodicalIF":8.6,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62525595","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}

引用次数: 0

Resource Allocation for Multi-Target Radar Tracking via Constrained Deep Reinforcement Learning 通过受限深度强化学习实现多目标雷达跟踪的资源分配

IF 8.6 1区计算机科学

IEEE Transactions on Cognitive Communications and Networking Pub Date : 2023-08-14 DOI: 10.1109/TCCN.2023.3304634

Ziyang Lu;M. Cenk Gursoy

{"title":"Resource Allocation for Multi-Target Radar Tracking via Constrained Deep Reinforcement Learning","authors":"Ziyang Lu;M. Cenk Gursoy","doi":"10.1109/TCCN.2023.3304634","DOIUrl":"10.1109/TCCN.2023.3304634","url":null,"abstract":"In this paper, multi-target tracking in a radar system is considered, and adaptive radar resource management is addressed. In particular, time management in tracking multiple maneuvering targets subject to budget constraints is studied with the goal to minimize the total tracking cost of all targets (or equivalently to maximize the tracking accuracies). The constrained optimization of the dwell time allocation to each target is addressed via deep Q-network (DQN) based reinforcement learning. In the proposed constrained deep reinforcement learning (CDRL) algorithm, both the parameters of the DQN and the dual variable are learned simultaneously. The proposed CDRL framework consists of two components, namely online CDRL and offline CDRL. Training a DQN in the deep reinforcement learning algorithm usually requires a large amount of data, which may not be available in a target tracking task due to the scarcity of measurements. We address this challenge by proposing an offline CDRL framework, in which the algorithm evolves in a virtual environment generated based on the current observations and prior knowledge of the environment. Simulation results show that both offline CDRL and online CDRL are critical for effective target tracking and resource utilization. Offline CDRL provides more training data to stabilize the learning process and the online component can sense the change in the environment and make the corresponding adaptation. Furthermore, a hybrid CDRL algorithm that combines offline CDRL and online CDRL is proposed to reduce the computational burden by performing offline CDRL only periodically to stabilize the training process of the online CDRL.","PeriodicalId":13069,"journal":{"name":"IEEE Transactions on Cognitive Communications and Networking","volume":"9 6","pages":"1677-1690"},"PeriodicalIF":8.6,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62525505","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}

引用次数: 0

IEEE Communications Society Information IEEE通信学会信息

IF 8.6 1区计算机科学

IEEE Transactions on Cognitive Communications and Networking Pub Date : 2023-08-07 DOI: 10.1109/TCCN.2023.3296949

引用次数: 0

IEEE Communications Society IEEE通信学会

IF 8.6 1区计算机科学

IEEE Transactions on Cognitive Communications and Networking Pub Date : 2023-08-07 DOI: 10.1109/TCCN.2023.3296951

引用次数: 0

Pattern Design and Power Management for Cognitive LEO Beaming Hopping Satellite-Terrestrial Networks 认知低地轨道波束跳频卫星-地面网络的模式设计和电源管理

IF 8.6 1区计算机科学

IEEE Transactions on Cognitive Communications and Networking Pub Date : 2023-07-28 DOI: 10.1109/TCCN.2023.3299576

Tong Li;Rugui Yao;Ye Fan;Xiaoya Zuo;Nikolaos I. Miridakis;Theodoros A. Tsiftsis

{"title":"Pattern Design and Power Management for Cognitive LEO Beaming Hopping Satellite-Terrestrial Networks","authors":"Tong Li;Rugui Yao;Ye Fan;Xiaoya Zuo;Nikolaos I. Miridakis;Theodoros A. Tsiftsis","doi":"10.1109/TCCN.2023.3299576","DOIUrl":"10.1109/TCCN.2023.3299576","url":null,"abstract":"The number of base stations (BSs) in remote areas is poor, and seamless coverage cannot be achieved. This paper investigates a cognitive satellite-terrestrial network, including the low earth orbit-beam hopping (BH) satellite and terrestrial systems. Besides, the weighted capacity-request ratio is regarded as the quality of service (QoS) in the satellite system, and the weight indicates channel quality and service priority. Similarly, the capacity-request ratio is introduced as the QoS in the terrestrial system. By establishing a relationship between beams and terminals, the solution space of the BH pattern and beam power is shrunk, and the power allocation competition algorithm is proposed. The proposed algorithm promptly obtains a better solution than the particle swarm optimization and genetic algorithms. As the secondary system, the terrestrial system should obtain an accurate sense of the satellite system. We design a dynamic-ratio threshold spectrum detection mechanism, which causes less miss detection than energy detection under co-channel interference (CCI). Moreover, based on CCI suppression and quick selection of greedy thought, an adaptive resource adjustment algorithm is determined for the BS pattern and transmit power. Finally, the efficiency of the proposed algorithms and spectrum detection mechanism is demonstrated in simulations.","PeriodicalId":13069,"journal":{"name":"IEEE Transactions on Cognitive Communications and Networking","volume":"9 6","pages":"1531-1545"},"PeriodicalIF":8.6,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62525494","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}

引用次数: 0

Computation Offloading and Resource Allocation Based on DT-MEC-Assisted Federated Learning Framework 基于 DT-MEC 辅助联合学习框架的计算卸载和资源分配

IF 8.6 1区计算机科学

IEEE Transactions on Cognitive Communications and Networking Pub Date : 2023-07-26 DOI: 10.1109/TCCN.2023.3298926

Yejun He;Mengna Yang;Zhou He;Mohsen Guizani

{"title":"Computation Offloading and Resource Allocation Based on DT-MEC-Assisted Federated Learning Framework","authors":"Yejun He;Mengna Yang;Zhou He;Mohsen Guizani","doi":"10.1109/TCCN.2023.3298926","DOIUrl":"10.1109/TCCN.2023.3298926","url":null,"abstract":"Traditional centralized machine learning uses a large amount of data for model training, which may face some privacy and security problems. On the other hand, federated learning (FL), which focuses on privacy protection, also faces challenges such as core network congestion and limited mobile device (MD) resources. The computation offloading technology of mobile edge computing (MEC) can effectively alleviate these challenges, but it ignores the effect of user mobility and the unpredictable MEC environment. In this paper, we first propose an architecture that combines digital twin (DT) and MEC technologies with the FL framework, where the DT network can virtually imitate the statue of physical entities (PEs) and network topology to be used for real-time data analysis and network resource optimization. The computation offloading technology of MEC is used to alleviate resource constraints of MDs and the core network congestion. We further leverage the FL to construct DT models based on PEs’ running data. Then, we jointly optimize the problem of computation offloading and resource allocation to reduce the straggler effect in FL based on the framework. Since the solution of the objective function is a stochastic programming problem, we model a Markov decision process (MDP), and use the deep deterministic policy gradient (DDPG) algorithm to solve this objective function. The simulation results prove the feasibility of the proposed scheme, and the scheme can significantly reduce the total cost by about 50% and improve the communication performance compared with baseline schemes.","PeriodicalId":13069,"journal":{"name":"IEEE Transactions on Cognitive Communications and Networking","volume":"9 6","pages":"1707-1720"},"PeriodicalIF":8.6,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62525438","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}

引用次数: 2

Joint Source-Channel Coding for a Multivariate Gaussian Over a Gaussian MAC Using Variational Domain Adaptation 利用变域自适应为高斯 MAC 上的多变量高斯进行源-信道联合编码

IF 8.6 1区计算机科学

IEEE Transactions on Cognitive Communications and Networking Pub Date : 2023-07-12 DOI: 10.1109/TCCN.2023.3294754

Yishen Li;Xuechen Chen;Xiaoheng Deng

{"title":"Joint Source-Channel Coding for a Multivariate Gaussian Over a Gaussian MAC Using Variational Domain Adaptation","authors":"Yishen Li;Xuechen Chen;Xiaoheng Deng","doi":"10.1109/TCCN.2023.3294754","DOIUrl":"10.1109/TCCN.2023.3294754","url":null,"abstract":"With the development of the distributed learning and edge computing, servers must often receive information from multiple terminal devices; thus, the importance of source-channel coding for distributed sources over multiple access channels (MACs) becomes more and more significant. This letter presents a deep joint source-channel coding (JSCC) design for a multivariate Gaussian source over a Gaussian MAC. The widely used autoencoder based deep-JSCC cannot perform stably under such conditions due to their easiness to fall into local optimum. Therefore we propose the variational domain adaptation (VDA)-JSCC scheme. Firstly, the loss function with an additional regularization term is introduced through variational analysis. The crucial prior distribution related to this item is obtained by domain adaptation, which is a transfer learning method. The proposed fine-tuning technique during the training process yields further performance improvement. Experiment results show that VDA-JSCC can always learn reasonable coding structures without artificial design and outperforms other state-of-the-art methods under different channel signal-to-noise ratios (CSNRs). We have also analyzed the reason why the performance of VDA-JSCC deteriorates in high CSNR range and then replace the encoder of VDA-JSCC with Mixture-of-Experts to improve its performance in high CSNR range. Finally, VDA-JSCC exhibits considerable robustness when the channel quality or correlation coefficient varies.","PeriodicalId":13069,"journal":{"name":"IEEE Transactions on Cognitive Communications and Networking","volume":"9 6","pages":"1424-1437"},"PeriodicalIF":8.6,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62525426","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}

引用次数: 0

Spectrum Sharing in Cache-Empowered Wireless Networks: Reservation-Based Versus Auction-Based Approaches 高速缓存无线网络中的频谱共享：基于预约与基于拍卖的方法

IF 8.6 1区计算机科学

IEEE Transactions on Cognitive Communications and Networking Pub Date : 2023-07-07 DOI: 10.1109/TCCN.2023.3293018

Haiming Hui;Xin Guo;Haiming Wang;Wei Chen

{"title":"Spectrum Sharing in Cache-Empowered Wireless Networks: Reservation-Based Versus Auction-Based Approaches","authors":"Haiming Hui;Xin Guo;Haiming Wang;Wei Chen","doi":"10.1109/TCCN.2023.3293018","DOIUrl":"10.1109/TCCN.2023.3293018","url":null,"abstract":"Spectrum sharing has attracted much recent attention from both industry and academia due to its significant potential of achieving high radio resource efficiency and scaling the service capability in wireless networks. However, how to fairly and efficiently share the radio spectrum or bandwidth in cache-empowered wireless networks remains open. In this paper, we present a reservation-based and an auction-based approach for dynamic spectrum access in cache-empowered wireless networks that serves both on-demand and pushing traffics. More specifically, a virtual network operator (VNO) is introduced as a spectrum access scheduler, which pays to the spectrum owner for the bandwidth it uses while charging its users for their content requests. To ensure the quality of service, a VNO is punished if it fails to satisfy a user’s request in peak time. By balancing the bandwidth cost and penalty, multiple VNOs may maximize the spectrum efficiency in a distributed manner. To further improve the spectrum efficiency in cache-empowered wireless networks, we formulate a linear program and a nonlinear program for both the reservation-based and the auction-based spectrum access, respectively. A modified deep Q-network algorithm is also presented to substantially reduce the computational complexity and to attain a distributed online spectrum sharing protocol.","PeriodicalId":13069,"journal":{"name":"IEEE Transactions on Cognitive Communications and Networking","volume":"9 5","pages":"1126-1140"},"PeriodicalIF":8.6,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46566791","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}

引用次数: 0