检索结果-内蒙古大学图书馆

Frame Generation Algorithm for Differentiated Services in Tactical Communication Networks

Journal of Communications and Information Networks 2025年第1期10卷 15-25页

作者： Huaifeng Shi Chengsheng Pan Lishang Qin Yingzhi Wang Huangjie Lu Key Laboratory of Intelligent Support Technology for Complex Environments Ministry of EducationNanjing University of Information Science and TechnologyNanjing 210044China

In response to the complex and multidimensional nature of converged traffic on heterogeneous links in tactical communication networks,which leads to the difficulty in ensuring the quality of service(QoS)requirements for critical services,a frame generation algorithm for differentiated services(DS-FG)is ***-FG deploys an adaptive frame generation algorithm based on deep reinforcement learning(DRL-FG)for timesensitive service,while deploying a high efficient frame generation(HEFG)algorithm for non-time-sensitive ***-FG constructs a reward function by combining the queue status information of time-sensitive service and utilizes deep deterministic policy gradients(DDPG)to train a decision model for adaptive frame generation(AFG)algorithm ***,Gaussian noise sampling and prioritized experience replay strategies are employed to enhance model training efficiency and performance,achieving optimal matching between time-sensitive service QoS requirements and frame generation *** results demonstrate that DS-FG outperforms traditional algorithms,achieving up to 13%improvement in throughput and over 19.7%reduction in average queueing delay for time-sensitive service.

关键词： frame generation algorithm tactical communication network reinforcement learning differentiated services

来源：评论

学校读者我要写书评

暂无评论

WF-A2D: Enhancing Privacy with Asymmetric Adversarial Defense Against Website Fingerprinting

引用

IEEE Transactions on Information Forensics and Security 2025年 20卷 4739-4754页

作者： Huang, Jianan Liu, Weiwei Liu, Guangjie Gao, Bo Nie, Fengyuan Nanjing University of Science and Technology School of Automation Nanjing210094 China Nanjing University of Information Science and Technology School of Electronics and Information Engineering Nanjing210044 China Key Laboratory of Intelligent Support Technology for Complex Environments Ministry of Education Nanjing210044 China

Despite the end-to-end encryption capabilities provided by network protocols such as QUIC in HTTP/3 and the additional tunneling functions offered by proxy tools like virtual private networks (VPNs) and the onion router (Tor), website fingerprinting (WF) techniques can still identify specific network services by exploiting the spatio-temporal characteristics of network traffic. Therefore, defending against WF attacks is crucial for ensuring comprehensive privacy protection for network services. Existing WF defenses typically rely on proxy-based solutions that require coordinated packet manipulations between the client and the proxy node to counteract WF attacks. These symmetric architectures cannot protect network traffic between proxy nodes and web servers from WF attacks. Furthermore, the ability to counter more powerful traffic analysis tools remains a challenging issue. In this paper, we propose WF-A2D, an asymmetric adversarial defense method against website fingerprinting for HTTP/3. WF-A2D employs a two-stage cascading adversarial learning strategy, leveraging packet direction and length patterns to enhance defense performance. Position-based perturbation vectors representing packet operations are generated for packet-by-packet manipulations to achieve real-time WF defense. Experimental results on a real-world HTTP/3-QUIC website browsing traffic dataset demonstrate that WF-A2D can achieve a defense success rate of 97.10% on average against seven state-of-the-art traffic analysis tools, while incurring less than 2% bandwidth overhead. More importantly, WF-A2D can operate independently on the client side and ensure end-to-end protection to web servers. © 2005-2012 IEEE.

关键词： HTTP

来源：评论

学校读者我要写书评

暂无评论

QuicCourier: Leveraging the Dynamics of QUIC-Based Website Browsing Behaviors Through Proxy for Covert Communication

引用

IEEE Transactions on Dependable and Secure Computing 2025年

作者： Huang, Jianan Liu, Weiwei Liu, Guangjie Gao, Bo Nie, Fengyuan Nanjing University of Science and Technology School of Automation Nanjing210094 China Nanjing University of Information Science and Technology School of Electronics and Information Engineering Nanjing210044 China Ministry of Education Key Laboratory of Intelligent Support Technology for Complex Environments Nanjing China

Network covert channels transmit secret messages by manipulating network traffic, including packet headers, timing intervals, and communication patterns. The growth of network services has spurred interest in exploring these channels. Yet, the practical application of these channels faces challenges in transmission rate and reliability due to unpredictable network interference. QUIC-based websites offer promising opportunities for covert communication, given their inherent dynamic nature from web resource updates and network interferences. Repeated visits or refresh actions on the same website generate substantial statistical redundancy. Furthermore, widely used proxy tools introduce additional traffic morphology changes. This paper presents QuicCourier, a covert channel leveraging web traffic's dynamic characteristics and proxy service encapsulation to hide messages in QUIC packets from the service node to the client. Guided by a generative model for web resource patterns, QuicCourier ensures that covert traffic closely resembles legitimate traffic, employing three packet-wise meta operations. The altered QUIC flows are then encased in proxy protocols, complicating the detection of embedded information. The covert receiver is incorporated into the proxy client. The efficacy of QuicCourier is evaluated using a dataset of over 30,000 web browsing traffic samples, demonstrating its exceptional undetectability against state-of-the-art traffic classification tools and a high covert transmission rate. © 2004-2012 IEEE.

关键词： Websites

来源：评论

学校读者我要写书评

暂无评论

Contract-Based Incentive Mechanisms for UAV Networks in Covert Communications

引用

IEEE Transactions on Vehicular technology 2025年第5期74卷 7378-7391页

作者： Tian, Wen Fan, Hao Liu, Guangjie Du, Miao Liu, Yinqiu Niyato, Dusit Han, Zhu Nanjing University of Information Science and Technology School of Electronic and Information Engineering Nanjing University of Information Science and Technology Key Laboratory of Intelligent Support Technology In Complex Environment Ministry of Education Nanjing210044 China Southeat University School of Computer Science and Engineering China Southeast University Key Laboratory of Computer Network and Information Integration Ministry of Education Nanjing China Nanyang Technological University School of Computer Science and Engineering 639798 Singapore University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

Covert communication is considered a promising technology for hiding transmission processes and activities from malicious eavesdropping. With the development of detection technology, the traditional point-to-point covert communication method cannot effectively guarantee the reliability of covert communication. In order to solve this problem, unmanned aerial vehicle (UAV) are widely adopted in covert communication as common relay equipment. However, the UAV maximizes its benefits by taking advantage of the information asymmetry between itself and the covert communication sender. Therefore, it is necessary to encourage UAV-assisted potential users (UPU) to transmit covert data honestly by designing an information asymmetry-based incentive mechanism. In this paper, we propose a UAV-assisted contract-theoretic (UACT) model to improve the covert communication performance, where UPU honestly transmits covert data and the throughput of UACT can be increased. Specifically, we first divide UPU into finite types and model the data transfer contract between the sender, UPU, and receiver. Then, the contract feasibility of UACT is derived with sufficient and necessary conditions. Finally, we analyze the contract optimization in the continuous case of UPUs. Numerical simulations show that the UACT can incentivize UPUs to transmit covert data through UAV assistance and make covert communication performance close to the information symmetry case. © 1967-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

IoT-AMLHP: Aligned Multimodal Learning of Header-Payload Representations for Resource-Efficient Malicious IoT Traffic Classification

arXiv

引用

arXiv 2025年

作者： Nie, Fengyuan Liu, Guangjie Liu, Weiwei Huang, Jianan Gao, Bo School of Automation Nanjing University of Science and Technology Nanjing210094 China School of Electronics and information engineering Nanjing University of Information Science and Technology Nanjing210044 China Key Laboratory of Intelligent Support Technology for Complex Environments Ministry of Education Nanjing University of Information Science and Technology Jiangsu Nanjing210044 China

Traffic classification is crucial for securing Internet of Things (IoT) networks. Deep learning-based methods can autonomously extract latent patterns from massive network traffic, demonstrating significant potential for IoT traffic classification tasks. However, the limited computational and spatial resources of IoT devices pose challenges for deploying more complex deep learning models. Existing methods rely heavily on either flow-level features or raw packet byte features. Flow-level features often require inspecting entire or most of the traffic flow, leading to excessive resource consumption, while raw packet byte features fail to distinguish between headers and payloads, overlooking semantic differences and introducing noise from feature misalignment. Therefore, this paper proposes IoT-AMLHP, an aligned multimodal learning framework for resource-efficient malicious IoT traffic classification. Firstly, the framework constructs a packet-wise header-payload representation by parsing packet headers and payload bytes, resulting in an aligned and standardized multimodal traffic representation that enhances the characterization of heterogeneous IoT traffic. Subsequently, the traffic representation is fed into a resource-efficient neural network comprising a multimodal feature extraction module and a multimodal fusion module. The extraction module employs efficient depthwise separable convolutions to capture multi-scale features from different modalities while maintaining a lightweight architecture. The fusion module adaptively captures complementary features from different modalities and effectively fuses multimodal features. Extensive experiments on three public IoT traffic datasets demonstrate that the proposed IoT-AMLHP outperforms state-of-the-art methods in classification accuracy while significantly reducing computational and spatial resource overhead, making it highly suitable for deployment in resource-constrained IoT environments. Copyright © 2025, The Autho

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Optimal Flying Location for Unmanned Aerial Vehicle Equipped with MF-RIS assisted Covert Wireless on Communication

引用

IEEE Transactions on Vehicular technology 2025年

作者： Wang, Jie Li, Yunxiang Tian, Wen Dai, Yuewei Liu, Yinqiu Niyato, Dusit Nanjing University of Posts and Telecommunications School of Communications and Information Engineering Nanjing China Nanjing University of Information Science and Technology School of Electronic and Information Engineering Key Laboratory of Intelligent Support Technology In Complex Environment Ministry of Education Nanjing210044 China Nanyang Technological University College of Computing and Data Science Singapore

In the current information age, covert communication holds significant value owing to its advantages, such as heightened security, enhanced flexibility, and improved concealment, surpassing those of traditional communication methods. However, existing covert communication approaches approximate communication channel models by Line-of-Sight (LoS) links, which is insufficient due to neglecting the impact of multipath effects and applying inaccurate performance assessments. To better adapt to real-world communication channel conditions, we propose a novel covert communication model assisted by Unmanned Aerial Vehicles (UAV) equipped with Multi-Functional Reconfigurable intelligent Surface (MF-RIS), named UMCCM. Specifically, based on a mixed link of LoS and Non-Line-of-Sight (NLoS), UMCCM leverages MF-RIS as a flexible relay to enhance the signal-to-noise ratio (SNR) and effective throughput. We first derive the mixed channel model expression. Then, we transform covert constraints from incomplete gamma functions to those linked with relative entropy and accordingly optimize the UAV transmission power and block length. Finally, the optimal flying position of the UAV is obtained by analyzing the functional properties of SNR and effective throughput under these refined constraints. Extensive numerical results demonstrate the superiority of our proposed UMCCM for enhancing SNR and effective throughput over the existing works. © 2025 IEEE.

关键词： Aircraft communication

来源：评论

学校读者我要写书评

暂无评论

IoT-AMLHP: Aligned multimodal learning of header-payload representations for resource-efficient malicious IoT traffic classification

引用

Ad Hoc Networks 2025年

作者： Fengyuan Nie Guangjie Liu Weiwei Liu Jianan Huang Bo Gao School of Automation Nanjing University of Science and Technology Nanjing 210094 China School of Electronics and information engineering Nanjing University of Information Science and Technology Nanjing 210044 China Key Laboratory of Intelligent Support Technology for Complex Environments Ministry of Education Nanjing University of Information Science and Technology Nanjing 210044 Jiangsu China

关键词：

来源：评论

学校读者我要写书评

暂无评论

Boosting Adversarial Training with Learnable Distribution

引用

Computers, Materials & Continua 2024年第3期78卷 3247-3265页

作者： Kai Chen Jinwei Wang James Msughter Adeke Guangjie Liu Yuewei Dai School of Electronics and Information Engineering Nanjing University of Information Science and TechnologyNanjing210044China Key Laboratory of Intelligent Support Technology for Complex Environments Ministry of EducationNanjing210044China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China Nanjing Center for Applied Mathematics Nanjing211135China

In recent years,various adversarial defense methods have been proposed to improve the robustness of deep neural *** training is one of the most potent methods to defend against adversarial ***,the difference in the feature space between natural and adversarial examples hinders the accuracy and robustness of the model in adversarial *** paper proposes a learnable distribution adversarial training method,aiming to construct the same distribution for training data utilizing the Gaussian mixture *** distribution centroid is built to classify samples and constrain the distribution of the sample *** natural and adversarial examples are pushed to the same distribution centroid to improve the accuracy and robustness of the *** proposed method generates adversarial examples to close the distribution gap between the natural and adversarial examples through an attack algorithm explicitly designed for adversarial *** algorithm gradually increases the accuracy and robustness of the model by scaling ***,the proposed method outputs the predicted labels and the distance between the sample and the distribution *** distribution characteristics of the samples can be utilized to detect adversarial cases that can potentially evade the model *** effectiveness of the proposed method is demonstrated through comprehensive experiments.

关键词： Adversarial training feature space learnable distribution distribution centroid

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：