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Satellite Internet (SAT-NET), International Conference on

作者： Zewei Guo Ranran Sun Ji He Yulong Shen Xiaohong Jiang School of Systems Information Science Future University Hakodate Hakodate Japan Hangzhou Institute of Technology Xidian University Hangzhou China School of Computer Science and Technology Xidian University Xi’an China Academy of Military Sciences Institute of Systems General Academy of Systems Engineering Beijing China Shaanxi Key Laboratory of Network and System Security Xidian University Xi’an China

ISBN: (数字)9798350375176

ISBN: (纸本)9798350387469

This paper investigates the covert communication in a satellite-terrestrial system, including a satellite transmitter Alice, a terrestrial full-duplex receiver Bob and a terrestrial warden Willie. To help the covert transmission from Alice, the full-duplex Bob transmits the jamming signal to confuse Willie and also receives the signal from Alice simultaneously. To explore the fundamental covertness in such a system, we first provide theoretical modelings for satellite-terrestrial downlink, and the detection error probability of Willie. Based on these models, we then study the transmit power optimization for covert rate maximization. Finally, we present extensive numerical results to validate our theoretical analysis and to illustrate the impact of various system parameters on the maximum covert rate.

关键词： Satellites Error probability Transmitters Full-duplex system Receivers Space-air-ground integrated networks Downlink Numerical models Jamming Optimization

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Cross-Layer security for Semantic Communications: Metrics and Optimization

arXiv

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arXiv 2025年

作者： Wang, Lingyi Wu, Wei Zhou, Fuhui Qin, Zhijin Wu, Qihui College of Science Nanjing University of Posts and Telecommunications Nanjing210003 China College of Communication and Information Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Anhui Province Key Laboratory of Cyberspace Security Situation Awareness and Evaluation China College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing210000 China Department of Electronic Engineering Tsinghua University Beijing100084 China Beijing National Research Center for Information Science and Technology Beijing China The State Key Laboratory of Space Network and Communications Beijing China

Different from traditional secure communication that focuses on symbolic protection at the physical layer, semantic secure communication requires further attention to semantic-level task performance at the application layer. There is a research gap on how to comprehensively evaluate and optimize the security performance of semantic communication. In order to fill this gap, a unified semantic security metric, the cross-layer semantic secure rate (CLSSR), is defined to estimate cross-layer security requirements at both the physical layer and the application layer. Then, we formulate the maximization problem of the CLSSR with the mixed integer nonlinear programming (MINLP). We propose a hierarchical AI-native semantic secure communication network with a reinforcement learning (RL)based semantic resource allocation scheme, aiming to ensure the cross-layer semantic security (CL-SS). Finally, we prove the convergence of our proposed intelligent resource allocation, and the simulation results demonstrate that our proposed CLSS method outperforms the traditional physical layer semantic security (PL-SS) method in terms of both task reliability and CLSSR. Copyright © 2025, The Authors. All rights reserved.

关键词： Mixed-integer linear programming

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Full-scale studies are closer to reality than lab-scale ones: Tertiary treatment constructed wetlands maintain robust removal capability for pharmaceuticals and personal care products in cold weather conditions

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Bioresource technology 2025年 432卷 132661页

作者： Wang, Jiaxi Ye, Beibei Yu, Xia Yan, Ruiqi Lin, Hui Man, Ying Sui, Qian State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process School of Resources and Environmental Engineering East China University of Science and Technology Shanghai200237 China Beijing100015 China School of Chemistry and Environment Guangdong Ocean University Zhanjiang524088 China Shanghai Institute of Pollution Control and Ecological Security Shanghai200092 China

In contrast to previous lab-scale studies, full-scale studies show that low temperatures do not significantly hinder pharmaceutical and personal care product (PPCP) removal in tertiary treatment constructed wetland (CW) systems. This study investigated PPCP removal pathways (substrate adsorption, plant uptake, microbial degradation) in two full-scale CWs, highlighting the differences between full-scale and lab-scale study outcomes. Results demonstrated that low temperatures did not adversely affect PPCP removal in full-scale CWs. Substrate adsorption was minimally impacted at a relevant concentration of 100 ng/L, unlike lab-scale studies with typically higher concentrations (1 mg/L). Plant uptake was not affected, as mature plants in CWs exhibited a lower PPCP uptake capacity compared to seedlings in lab-scale studies. Furthermore, low temperatures did not reduce microbial biodegradation performance. However, low temperatures increased dissolved oxygen concentrations in the influent, supporting aerobic microbial activity. These findings emphasize the value of full-scale CWs for stable PPCP removal under low-temperature conditions. © 2025

关键词： Inclusions

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Deep Learning Algorithms Design and Implementation Based on Differential Privacy 3rd

Deep Learning Algorithms Design and Implementation Based on ...

引用

3rd International Conference on Machine Learning for Cyber security, ML4CS 2020

作者： Xu, Xuefeng Yao, Yanqing Cheng, Lei Key Laboratory of Aerospace Network Security Ministry of industry and information technology School of Cyberspace Science and Technology Beihang University Beijing100191 China State Key Laboratory of Software Development Environment Beihang University Beijing100191 China Beijing Key Laboratory of Network Technology Beihang University Beijing China Shenzhen Research Institute of Big Data Shenzhen518000 China

ISBN: (纸本)9783030622220

Deep learning models bear the risks of privacy leakage. Attackers can obtain sensitive information contained in training data with some techniques. However, existing differentially private methods such as Differential Privacy-Stochastic Gradient Descent (DP-SGD) and Differential Privacy-Generative Adversarial network (DP-GAN) are not very efficient as they require to perform sampling multiple times. More importantly, DP-GAN algorithm need public data to set gradient clipping threshold. In this paper, we introduce our refined algorithms to tackle these problems. First, we employ random shuffling instead of random sampling to improve training efficiency. We also test Gaussian and Laplace Mechanisms for clipping gradients and injecting noise. Second, we employ zero Concentrated Differential Privacy (zCDP) to compute overall privacy budget. Finally, we adopt dynamical gradient clipping in DP-GAN algorithm. During each iteration, we random sample training examples and set the average gradients norm as the new threshold. This not only makes the algorithm more robust but also doesn’t increase the overall privacy budget. We experiment with our algorithms on MNIST data sets and demonstrate the accuracies. In our refined DP-SGD algorithm, we achieve test accuracy of 96.58%. In our refined DP-GAN algorithm, we adopt the synthetic data to train models and reach test accuracy of 91.64%. The results show that our approach ensures model usability and provides the capability of privacy protection. © 2020, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

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Multi-dimensional Intelligent network Asset Identification

Multi-dimensional Intelligent Network Asset Identification

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IEEE International Conference on Data Science in Cyberspace (DSC)

作者： Yi Xiong Xiaoyan Zhang Ling Pang Zhechao Lin Topsec Network Technology Inc. Beiijng China National Key Laboratory of Science and Technology on Information System Security BeijingChina

ISBN: (纸本)9781665418164

In the field of cyberspace detection and identification, how to improve the accuracy of asset identification is always a great challenge for people. This paper proposes a multi-input fusion model based on TextRCNN, which uses multi-dimensional features to identify asset types, so as to improve the accuracy of the identification. Firstly, we analyze many kinds of assets and select the protocols with symbolic characteristics. The data set is obtained based on the detection results of the selected protocols. Then, the deep learning multi-input fusion model is constructed for training. Finally, on the basis of active detection and identification technology, this model is used to improve the accuracy and credibility of asset type identification. The characteristics of this method are as follows: the fusion network can process multi-protocol input data at the same time, so as to build a multi-dimensional identification model; the identification of key attributes of assets is based on multi-dimensional characteristics, and no longer depends on the identification result of a single port. The experimental results show that the accuracy of the multi-dimensional intelligent recognition method can reach 89.48%, which can effectively identify the asset types.

关键词： Training Deep learning Intelligent networks Protocols Conferences Cyberspace Data science

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On the Effectiveness of Function-Level Vulnerability Detectors for Inter-Procedural Vulnerabilities

arXiv

引用

arXiv 2024年

作者： Li, Zhen Wang, Ning Zou, Deqing Li, Yating Zhang, Ruqian Xu, Shouhuai Zhang, Chao Jin, Hai School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Department of Computer Science University of Colorado Colorado Springs Colorado SpringsCO United States Institute for Network Sciences and Cyberspace Tsinghua University Beijing China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security Cluster and Grid Computing Lab China JinYinHu Laboratory Wuhan China

Software vulnerabilities are a major cyber threat and it is important to detect them. One important approach to detecting vulnerabilities is to use deep learning while treating a program function as a whole, known as function-level vulnerability detectors. However, the limitation of this approach is not understood. In this paper, we investigate its limitation in detecting one class of vulnerabilities known as inter-procedural vulnerabilities, where the to-be-patched statements and the vulnerability-triggering statements belong to different functions. For this purpose, we create the first Inter-Procedural Vulnerability Dataset (InterPVD) based on C/C++ open-source software, and we propose a tool dubbed VulTrigger for identifying vulnerability-triggering statements across functions. Experimental results show that VulTrigger can effectively identify vulnerability-triggering statements and inter-procedural vulnerabilities. Our findings include: (i) inter-procedural vulnerabilities are prevalent with an average of 2.8 inter-procedural layers;and (ii) function-level vulnerability detectors are much less effective in detecting to-be-patched functions of inter-procedural vulnerabilities than detecting their counterparts of intra-procedural vulnerabilities. Copyright © 2024, The Authors. All rights reserved.

关键词： Open source software

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A joint call for actions to advance taxonomy in China

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Zoological Systematics 2022年第3期47卷 188-197页

作者： Chaodong Zhu Arong Luo Ming Bai Michael COrr Zhonge Hou Siqin Ge Jun Chen Yibo Hu Xuming Zhou Gexia Qiao Hongzhi Kong Limin Lu Xiaohua Jin Lei Cai Xinli Wei Ruilin Zhao Wei Miao Qingfeng Wang Zhongli Sha Qiang Lin Meng Qu Jianping Jiang Jiatang Li Jing Che Xuelong Jiang Xiaoyong Chen Lianming Gao Zongxin Ren Chunlei Xiang Shixiao Luo Donghui Wu Dong Liu Yanqiong Peng Tao Su Chenyang Cai Tianqi Zhu Wanzhi Cai Xingyue Liu Hu Li Huaijun Xue Zhen Ye Xuexin Chen Pu Tang Shujun Wei Hong Pang Qiang Xie Feng Zhang Feng Zhang Xianjin Peng Aibing Zhang Taiping Gao Changfa Zhou Chen Shao Libin Ma Zhaoming Wei Yunxia Luan Ziwei Yin Wu Dai Cong Wei Xiaolei Huang Jingxian Liu Xiangsheng Chen Tianci Yi Zhisheng Zhang Zhulidezi Aishan Qin Li Hongying Hu CAS Key Laboratory of Zoological Systematics and Evolution Institute of ZoologyChinese Academy of SciencesBeijing 100101China CAS Key Laboratory of Animal Ecology and Conservation Biology Institute of ZoologyChinese Academy of SciencesBeijing 100101China State Key Laboratory of Systematic and Evolutionary Botany Institute of BotanyChinese Academy of SciencesBeijing 100093China State Key Laboratory of Mycology(SKLM) Institute of MicrobiologyChinese Academy of SciencesBeijing 100101China CAS Key Laboratory of Aquatic Biodiversity and Conservation Institute of HydrobiologyChinese Academy of SciencesWuhan 430072China Wuhan Botanical Garden Chinese Academy of SciencesWuhan 430074China Department of Marine Organism Taxonomy&Phylogeny Institute of OceanologyChinese Academy of SciencesQingdao 266071China CAS Key Laboratory of Tropical Marine Bio-resources and Ecology South China Sea Institute of OceanologyChinese Academy of SciencesGuangzhou 510301China CAS Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization&Ecological Restoration and Biodiversity Conservation Key Laboratory of Sichuan Province Chengdu Institute of BiologyChinese Academy of SciencesChengdu 610041China State Key Laboratory of Genetic Resources and Evolution&Yunnan Key Laboratory of Biodiversity and Ecological Security of Gaoligong Mountain Kunming Institute of ZoologyChinese Academy of SciencesKunming 650221China CAS Key Laboratory for Plant Diversity and Biogeography of East Asia Kunming Institute of BotanyChinese Academy of SciencesKunming 650201China CAS Key Laboratory of Plant Resource Conservation and Sustainable Utilization South China Botanical GardenChinese Academy of SciencesGuangzhou 510650China CAS Key Laboratory of Wetland Ecology and Environment Northeast Institute of Geography and AgroecologyChinese Academy of SciencesChangchun 130102China CAS Key Laboratory of Tropical Forest Ecology Xishuangbanna Tropical Botanical GardenChinese Academy of SciencesMenglunMenglaYunnan 66630

Taxonomy plays an important role in understanding the origin, evolution, and ecological functionality of biodiversity. There are large number of unknown species yet to be described by taxonomists, which together with their ecosystem services cannot be effectively protected prior to description. Despite this, taxonomy has been increasingly underrated insufficient funds and permanent positions to retain young talents. Further, the impact factordriven evaluation systems in China exacerbate this downward trend, so alternative evaluation metrics are urgently necessary. When the current generation of outstanding taxonomists retires,there will be too few remaining taxonomists left to train the next generation. In light of these challenges, all co-authors worked together on this paper to analyze the current situation of taxonomy and put out a joint call for immediate actions to advance taxonomy in China.

关键词： Endangered taxonomists morphology-based taxonomy integrative taxonomy capacity building systematics

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On the Effectiveness of Function-Level Vulnerability Detectors for Inter-Procedural Vulnerabilities

On the Effectiveness of Function-Level Vulnerability Detecto...

引用

International Conference on Software Engineering (ICSE)

作者： Zhen Li Ning Wang Deqing Zou Yating Li Ruqian Zhang Shouhuai Xu Chao Zhang Hai Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security Cluster and Grid Computing Lab School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Jin YinHu Laboratory Wuhan China Department of Computer Science University of Colorado Colorado Springs Colorado Springs Colorado USA Institute for Network Sciences and Cyberspace Tsinghua University Beijing China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798400702174

ISBN: (纸本)9798350382143

Software vulnerabilities are a major cyber threat and it is important to detect them. One important approach to detecting vulnerabilities is to use deep learning while treating a program function as a whole, known as function-level vulnerability detectors. However, the limitation of this approach is not understood. In this paper, we investigate its limitation in detecting one class of vulnerabilities known as inter-procedural vulnerabilities, where the to-be-patched statements and the vulnerability-triggering statements belong to different functions. For this purpose, we create the first Inter -Procedural Vulnerability Dataset (InterPVD) based on C/C++ open-source software, and we propose a tool dubbed VulTrigger for identifying vulnerability-triggering statements across functions. Experimental results show that VulTrigger can effectively identify vulnerability-triggering statements and inter-procedural vulnerabilities. Our findings include: (i) inter-procedural vulnerabilities are prevalent with an average of 2.8 inter-procedural layers; and (ii) function-level vulner-ability detectors are much less effective in detecting to-be-patched functions of inter-procedural vulnerabilities than detecting their counterparts of intra-procedural vulnerabilities.

关键词： Deep learning Detectors Open source software Software engineering

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Towards practical anonymous quantum communication: A measurement-device-independent approach

引用

Physical Review A 2021年第5期104卷 052415-052415页

作者： Yu-Guang Yang Xiao-Xiao Liu Shang Gao Yi-Hua Zhou Wei-Min Shi Jian Li Dan Li Faculty of Information Technology Beijing University of Technology Beijing 100124 China Beijing Key Laboratory of Trusted Computing Beijing 100124 China College of Network Security Beijing University of Posts and Telecommunications Beijing 100876 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing 210016 China

The multipartite Greenberger-Horne-Zeilinger (GHZ) entangled state is an important resource for anonymous quantum communication tasks. But its low intensity and fragility limit the practical applications of these anonymous communication tasks under current conditions. Here, we present a feasible anonymous communication protocol in the measurement-device-independent framework. We analyze its performance in a quantum network under certain types of noise. Then we compare the performance of our protocol with the GHZ-state-based anonymous protocol. We demonstrate that our protocol has a unique advantage, i.e., it can tolerate an arbitrary number of nonresponsive nodes. We prove that the security of our protocol in an active adversary scenario in which active malicious agents and an untrusted ancillary node are taken into account. Utilizing the measurement-device-independent technology, our proposal suggests an important avenue for practical anonymous quantum communication.

关键词： Quantum communication Quantum cryptography

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Solving Modular Linear Equations via Automated Coppersmith and Its Applications 20th

Solving Modular Linear Equations via Automated Coppersmith ...

引用

20th International Conference on Information security and Cryptology, Inscrypt 2024

作者： Feng, Yansong Liu, Zhen Nitaj, Abderrahmane Pan, Yanbin State Key Laboratory of Mathematical Sciences Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing China Hubei Provincial Engineering Research Center of Intelligent Connected Vehicle Network Security School of Cyber Science and Technology Hubei University Wuhan430062 China Normandie Univ UNICAEN CNRS LMNO Caen14000 France

ISBN: (纸本)9789819647330

At Asiacrypt’23, Meers and Nowakowski introduced a new automated method called Automated Coppersmith, which can be viewed as a generalization of Jochemsz-May Strategy for systems of polynomial equations. It selects monomials first, then constructs polynomials to construct the lattice in Coppersmith’s method. However, their strategy raises a new heuristic assumption. In this paper, We try to eliminate this heuristic assumption on linear equation systems. Finally, we apply this method to analyze the Generalized Extended Implicit Factorization Problem (G-EIFP), a generalization of the Extended Implicit Factorization Problem (EIFP), even when the shared contiguous bits are arbitrary. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Linear equations

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