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Threshold Huffman-Based Covert Timing Channel Detection

International Journal of Network Security 2025年第1期27卷 61-71页

作者： Lin, Yuwei Chen, Yonghong Zhuang, Xiaolong huang, xuwen School of Computer Science and Technology Huaqiao University Fujian Xiamen361000 China Xiamen Key Laboratory of Data Security and Blockchain Technology Huaqiao University Fujian Xiamen361000 China

Network covert timing channels in computer networks evade effective detection by traditional security mechanisms such as firewalls, posing a significant threat to network security. However, most existing methods struggle to detect such channels when the window size is small. Additionally, the emergence of the new ϵ-κlibur channel has resulted in a decline in performance for detection methods such as GAS, SnapCatch, and DNN when detecting this particular channel. In this paper, we investigate a Huffman tree-based approach for detecting anomalous nodes in traffic and achieving the classification of channels through the design of weight intervals. Our method achieves an average detection rate of over 95% for each channel. Additionally, compared to GAS, SnapCatch, and DNN, our method improves the detection rates for the ϵ-κlibur channel by 11.75%, 8.46%, and 4.81%, respectively. The experimental results demonstrate that our proposed approach successfully detects ϵ-κlibur and achieves detection in a small window. © (2025), (Femto Technique Co., Ltd.). All rights reserved.

关键词： Computer system firewalls

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ConTra: A Covert Timing Channel Detection Approach for Little Covert Information in a Network 23

ConTra: A Covert Timing Channel Detection Approach for Littl...

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4th International Conference on Computing, Networks and Internet of Things, CNIOT 2023

作者： Li, Zhiqiang Chen, Yonghong Teng, Zhan huang, xuwen School of Computer Science and Technology Huaqiao University Xiamen Fujian China Xiamen Key Laboratory of Data Security and Blockchain Technology Huaqiao University Xiamen Fujian China

ISBN: (纸本)9798400700705

A covert timing channel is a technical means that enables information hiding and covert communication. Due to the fact that covert timing channels can elude detection by security defence measures, they offer a substantial security risk to the information of Internet users when they are exploited for illicit reasons. The attacker sends at a low rate to ensure the stealthiness of the covert timing channel communication process, making the number of inter-arrival time encoded as covert information much less than the normal number of inter-arrival time, resulting in the low detection accuracy of existing detection methods. In this paper, we propose a covert timing channel detection method based on one-dimensional convolution and self-attention mechanism. The method begins with local feature extraction of the input inter-arrival time sequence by a one-dimensional convolutional layer, then characterizes the correlation between each inter-arrival time by a self-attention mechanism in the encoder, and finally through the full connection layer to produce the type output. In this study, experimental results on a public dataset and 16 self-built datasets demonstrate that the detection method delivers optimal detection results and efficient detection of covert information in low-volume communications. © 2023 ACM.

关键词： Optimal detection

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Detection of Network Time Covert Channels Based on Image Processing 23

Detection of Network Time Covert Channels Based on Image Pro...

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4th International Conference on Computing, Networks and Internet of Things, CNIOT 2023

作者： huang, xuwen Chen, Yonghong Li, Zhiqiang Zhan, Teng School of Computer Science and Technology Huaqiao University Xiamen Fujian China Xiamen Key Laboratory of Data Security and Blockchain Technology Huaqiao University Xiamen Fujian China

ISBN: (纸本)9798400700705

Network covert timing channels (NCTCs) utilize Inter-Packet Delay (IPD) encoding to hide data. It can be used for spreading malware and data leakage, posing severe threats to network security. With the increasing risk, the research on NCTC detection has become an important and urgent task. However, the detection methods based on IPD statistics are only effective for few types of channels and require large IPD sampling samples. The recent ML-based detection methods have multiple limitations due to their coarse-grained feature extraction method. In this paper, we propose a multi-channel image transformation method for extracting IPD features and select the lightweight network MobileVit for detection. We encode IPD one-dimensional time-series data into Gramian Angular Field (GAF), Markov Transition Field (MTF), and Recurrence plot (RP) images and stack them into dual-channel and three-channel images. After image transformation, we compare mainstream image classification networks and a self-built CNN. Experimental results show that our feature extraction image classification is more effective than the existing IPD extraction image transformation method. The MobileVit network shows better detection performance and accuracy, requiring fewer IPD sampling samples for detection windows. © 2023 ACM.

关键词： Sampling

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Fuzzy Hybrid Coyote Optimization Algorithm for Image Thresholding

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Computers, Materials & Continua 2022年第8期72卷 3073-3090页

作者： Linguo Li xuwen huang Shunqiang Qian Zhangfei Li Shujing Li Romany F.Mansour School of Computer Nanjing University of Posts and TelecommunicationsNanjing210003China School of Computer and Information Engineering Fuyang Normal UniversityFuyang236041China Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

In order to address the problems of Coyote Optimization Algorithm in image thresholding,such as easily falling into local optimum,and slow convergence speed,a Fuzzy Hybrid Coyote Optimization Algorithm(here-inafter referred to as FHCOA)based on chaotic initialization and reverse learning strategy is proposed,and its effect on image thresholding is *** chaotic initialization,the random number initialization mode in the standard coyote optimization algorithm(COA)is replaced by chaotic *** sequence is nonlinear and long-term unpredictable,these characteristics can effectively improve the diversity of the population in the optimization ***,in this paper we first perform chaotic initialization,using chaotic sequence to replace random number initialization in standard *** combining the lens imaging reverse learning strategy and the optimal worst reverse learning strategy,a hybrid reverse learning strategy is then *** the process of algorithm traversal,the best coyote and the worst coyote in the pack are selected for reverse learning operation respectively,which prevents the algorithm falling into local optimum to a certain extent and also solves the problem of premature *** on the above improvements,the coyote optimization algorithm has better global convergence and computational *** simulation results show that the algorithmhas better thresholding effect than the five commonly used optimization algorithms in image thresholding when multiple images are selected and different threshold numbers are set.

关键词： Coyote optimization algorithm image segmentation multilevel thresholding logistic chaotic map hybrid inverse learning strategy

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高质量推进中越跨境产业链合作:现状、挑战与对策研究

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东南亚纵横 2025年第1期 72-85页

作者：黄旭文广西社会科学院越南研究所广西南宁530022

随着全球经济一体化进程的推进,跨境产业链合作在中越两国经济发展中发挥着日益重要的作用。作为中国—东盟自由贸易区、《区域全面经济伙伴关系协定》(RCEP)和共建“一带一路”倡议下的重要合作伙伴,中越两国在产业合作、贸易往来和技... 详细信息

随着全球经济一体化进程的推进,跨境产业链合作在中越两国经济发展中发挥着日益重要的作用。作为中国—东盟自由贸易区、《区域全面经济伙伴关系协定》(RCEP)和共建“一带一路”倡议下的重要合作伙伴,中越两国在产业合作、贸易往来和技术转移等领域的协同发展逐步深化。特别是在制造业、绿色经济和数字经济等领域,中越合作展现出广泛的互补性和潜力。然而,在全球供应链重构、国际市场不确定性加剧,以及两国政策协调难度增加的背景下,中越跨境产业链合作面临诸多挑战。文章通过梳理中越跨境产业链的现状,系统分析两国在产业协同、技术创新及市场整合等方面的成效,并探讨合作中的瓶颈与挑战,在此基础上,进一步提出优化政策协调、加强技术创新、提升基础设施建设、加强国际合作及跨境人才培养等对策建议。

关键词：中越跨境产业链合作现状挑战对策建议

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Transform Sequential Data to Image for Detecting Covert Timing Channel

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International Journal of Network Security 2024年第2期26卷 224-234页

作者： huang, xuwen Chen, Yonghong Zhuang, Xiaolong Lin, Yuwei School of Computer Science and Technology Huaqiao University China Xiamen Key Laboratory of Data Security and Blockchain Technology Huaqiao University Xiamen Fujian 361000 China

The network covert timing channel utilizes inter-packet delay to encode binary data to achieve information leakage and other purposes. In recent years, Covert Timing Channels (CTCs) have been demonstrated to be applicable across various protocols and networks, posing a significant threat to network security. Simultaneously, new CTCs have challenged the efficacy of CTC detection schemes. The recent ϵ-κlibur and ϵ-κlibur-O channels exhibit structural and characteristic similarities to legitimate channels, rendering ML-based detection methods like GAS and Snap ineffective. In this paper, we investigate an approach based on Gramian Angular Field (GAF), Markov Transition Field (MTF), and Recurrence Plot (RP) image processing. We further employ the knowledge-distilled and compressed image classification model MobileVit for detection. Our approach achieves a detection rate 98.24% for seven different channels within a sampling window of 64 IPDs. Experimental results demonstrate our proposed scheme’s generality, sensitivity, and effectiveness. © 2024, Femto Technique Co.. All rights reserved.

关键词： Distillation

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福建省高速公路工程水土保持监理工作的实践与思考

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亚热带水土保持 2024年第2期36卷 46-48,54页

作者：黄旭文福州水保生态工程监理咨询有限公司福建福州350001

福建省具有独特的自然地理环境,而高速公路工程又具备“线型”工程兼具点、面结合的复杂特点,如不实行水土保持监理,无法保证工程水土保持方案设计的防治措施顺利实施。本文在福建省高速公路工程水土保持监理工作实践的基础上,总结经验... 详细信息

福建省具有独特的自然地理环境,而高速公路工程又具备“线型”工程兼具点、面结合的复杂特点,如不实行水土保持监理,无法保证工程水土保持方案设计的防治措施顺利实施。本文在福建省高速公路工程水土保持监理工作实践的基础上,总结经验提出高速公路工程水土保持监理存在的普遍问题,并结合笔者的工作实践给出针对性建议,以期能够为福建省后续高速公路建设水土保持监理工作提供借鉴。

关键词：福建省高速公路水土保持监理问题建议

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CircFBLN2 regulates duck myoblast proliferation and differentiation through miR-22-5p and MEF2C interaction

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POULTRY SCIENCE 2025年第5期104卷 105063页

作者： Liu, Shuibing Wu, Jintao Jiang, Hongxia Zhou, Ya'nan huang, xuwen Wang, Yuxiang Xie, Zhanbin Liao, Zurong Ding, Zhenxvan Liu, Jing Hu, Xiaolong Mao, Huirong Liu, Sanfeng Chen, Biao Jiangxi Agr Univ Coll Anim Sci & Technol Nanchang 330045 Jiangxi Peoples R China South China Agr Univ Coll Anim Sci Guangzhou 510642 Guangdong Peoples R China Jiangxi Agr Univ Poultry Inst Nanchang 330045 Peoples R China

The growth and development of duck skeletal muscle significantly affect duck meat production, making it essential to understand the molecular mechanisms underlying these processes. Circular RNAs (circRNAs) and microRNAs (miRNAs) are identified in many species and play essential roles in the regulation of myogenic processes;however, research on circRNAs and miRNAs involved in the duck skeletal muscle development is limited. In prior whole-transcriptome RNA sequencing study, we identified differential expression of miR-22-5p and the novel circular RNA circFBLN2, which arises from the second exon of the FBLN2 gene, in duck primary myoblasts (DPMs). In this study, we confirmed the circular structure of circFBLN2 and explored its expression patterns and functional implications in myogenesis. To elucidate the function of circFBLN2 in the myogenic processes of duck, we conducted experiments involving both the silencing and overexpression of circFBLN2 in DPMs. Our findings indicated that circFBLN2 inhibits DPM proliferation while promoting their differentiation. Conversely, when miR-22-5p was silenced and overexpressed, it exhibited opposing effects by promoting the proliferation of DPMs and inhibiting their differentiation. These results suggest a complex dynamic interplay between circFBLN2 and miR-22-5p in the regulation of DPMs proliferation and differentiation. Additionally, our results revealed that both circFBLN2 and myocyte enhancer factor 2 C (MEF2C) act as sponges for miR-22-5p, as demonstrated by binding predictions and dual-luciferase reporter assays. These results offer novel perspectives on the regulatory pathways underlying the duck embryonic skeletal muscle development, underscoring the pivotal function of circFBLN2 in the regulation of miR-22-5p expression. This research deepens our comprehension of the molecular underpinnings of avian myogenesis, potentially paving the way for more effective approaches to bolster growth and development of livestock.

关键词： Duck skeletal muscle circFBLN2 miR-22-5p MEF2C

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Fuzzy Multilevel Image Thresholding Based on Improved Coyote Optimization Algorithm

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IEEE ACCESS 2021年 9卷 33595-33607页

作者： Li, Linguo Sun, Lijuan Xue, Yu Li, Shujing huang, xuwen Mansour, Romany Fouad Nanjing Univ Posts & Telecommun Sch Comp Nanjing 210003 Peoples R China Fuyang Normal Univ Coll Informat Engn Fuyang 236041 Peoples R China Nanjing Univ Informat Sci & Technol Sch Comp & Software Nanjing 210044 Peoples R China Fuyang Normal Univ Coll Comp & Informat Engn Fuyang 236041 Peoples R China New Valley Univ Fac Sci Dept Math El Kharga 72511 Egypt

Due to the computational complexity of multilevel image thresholding, Swarm Intelligence Optimization Algorithm (SIOA) has been widely applied to improve the calculation efficiency. Therefore, more and more attention has been paid to exploring the application of the latest SIOA in multilevel segmentation. This article takes Otsu and fuzzy entropy as the objective functions, using Coyote Optimization Algorithm (COA) for multilevel thresholds optimization selection, through fuzzy median aggregation of local neighborhood information and then forms the Fuzzy Coyote Optimization Algorithm (FCOA), so that the thresholding image segmentation can be achieved in the end. To prevent the COA algorithm from falling into the local optimum, this article follows the differential evolution strategy adopted by the standard COA, using the number of iterations to construct the differential scaling factor to form the Improved Coyote Optimization Algorithm (ICOA). The experimental results show that fuzzy Kapur entropy and fuzzy median value aggregation-based ICOA(FICOA) achieves better image segmentation quality. Compared with Grey Wolf Optimizer (GWO), Fuzzy Modified Quick Artificial Bee Colony and Aggregation Algorithm (FMQABCA) and Fuzzy Modified Discrete Grey Wolf Optimizer and Aggregation Algorithm (FMDGWOA), FCOA and FICOA have certain advantages in visual effects of image segmentation and PSNR, FSIM evaluation indices. Particularly compared with GWO (also a wolf evolutionary algorithm), FICOA shows significant advantages.

关键词： Image segmentation Optimization Linear programming Entropy Particle swarm optimization Histograms Heuristic algorithms Coyote optimization algorithm information entropy image segmentation multilevel thresholding

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基于混沌初始化的改进郊狼算法在医学图像分割中的应用

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信息与电脑 2022年第3期34卷 65-67页

作者：黄旭文阜阳师范大学计算机与信息工程学院安徽阜阳236037

由于现有的医学图像分割方法效果不够理想,因此将混沌初始化的郊狼优化算法应用于医学图像分割中。对郊狼群参数进行混沌初始化处理,分析组内郊狼的成长情况,并评估新生郊狼的社会适应度。为了验证设计方法的有效性,进行对比实验。与模... 详细信息

由于现有的医学图像分割方法效果不够理想,因此将混沌初始化的郊狼优化算法应用于医学图像分割中。对郊狼群参数进行混沌初始化处理,分析组内郊狼的成长情况,并评估新生郊狼的社会适应度。为了验证设计方法的有效性,进行对比实验。与模糊改进的快速人工蜂群及其聚集算法(FMQABCA)、改进的模糊郊狼优化算法(FICOA)的图像分割结果相比,本文设计方法在医学图像分割方面具有更好的分割效果。

关键词：郊狼优化算法医学图像分割 Otsu Logistic混沌映射

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