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Threshold Password-Hardening Updatable Oblivious Key Management

IEEE Transactions on information Forensics and security 2025年 20卷 4799-4814页

作者： Jiang, Changsong Xu, Chunxiang Liu, Zhen Dong, Xinfeng Zhang, Wenzheng University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Singapore Management University School of Computing and Information Systems Bras Basah 188065 Singapore Huzhou313001 China Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100081 China Science and Technology on Communication Security Laboratory Chengdu610041 China

We propose a threshold password-hardening updatable oblivious key management system dubbed TPH-UOKM for cloud storage. In TPH-UOKM, a group of key servers share a user-specific secret key for a user, and assist the user in producing her/his password-derived private key in a threshold and oblivious way, where the password is hardened to resist offline dictionary guessing attacks. Anyone can outsource data protected with the user's password-derived public key to the cloud server, and merely the user holding the correct password can recover the password-derived private key for data access. TPH-UOKM can accomplish decryption of N ciphertexts with the complexity O(1) of communication between a user and the key servers, which outperforms existing schemes. TPH-UOKM supports password update. The cloud server can update all protected data of a user with an update token to be accessible only with the new password, which resists password leakage. We present a two-level proactivization mechanism to periodically update user-specific secret key shares and the key servers to thwart perpetual compromise of them, where the renewal of user-specific secret key shares reduces computation and communication costs compared to existing approaches. Provable security and high efficiency of TPH-UOKM are demonstrated by comprehensive analyses and performance evaluations. © 2005-2012 IEEE.

关键词： information management

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Transmit Rate Enhancement for STAR-RIS-Assisted Uplink NOMA

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IEEE Transactions on Vehicular technology 2025年第5期74卷 7651-7665页

作者： Feng, Youhong Xu, Longzhu Li, Qiang Yan, Shihao Wang, Hong Ng, Derrick Wing Kwan Anhui Normal University School of Physics and Electronic information Wuhu241000 China Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Edith Cowan University School of Science and Security Research Institute JoondalupWA6027 Australia Nanjing University of Posts and Telecommunications School of Communication and Information Engineering Nanjing210003 China University of New South Wales School of Electrical Engineering and Telecommunications SydneyNSW2033 Australia

In this paper, a novel simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) enhanced uplink non-orthogonal multiple access (NOMA) communication network is investigated. Specifically, we tackle the transmit rate maximization problem for the strong user, subject to the constraints on total power consumption and the successive interference cancellation order, while guaranteeing the minimum quality-of-service requirement for the weak user. To address such a non-convex optimal problem, we introduce a novel, efficient, and low-complexity scheme. Specifically, the power allocation and receive beamforming optimization solutions are acquired in closed forms, and the transmission and reflection coefficients are obtained in semi-closed forms with a one-dimensional bisection search. Then, theoretical analysis demonstrates our proposed scheme has a lower complexity compared to the schemes with alternating direction method of multipliers (ADMM) and semidefinite relaxation (SDR) strategies, and the complexity advantage of our proposed scheme over the SDR and ADMM aided schemes becomes prominent when the number of RIS elements increase. Simulation results show that the proposed STAR-RIS-NOMA scheme achieves a better performance than the conventional STAR-RIS-aided orthogonal multiple access (OMA) scheme and STAR-RIS aided NOMA scheme adopting random phase shifts. More specifically, the proposed STAR-RIS-NOMA scheme outperforms the STAR-RIS-OMA scheme in terms of the strong user's rate, especially when the quality-of-service (QoS) requirements for weak user is high, or there is a significant difference channel quality between the reflecting and transmitting links. © 1967-2012 IEEE.

关键词： Convex optimization

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OS-SEI: Open-Set Specific Emitter Identification Based on Outlier Exposure and Label Smoothing

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IEEE Internet of Things Journal 2025年

作者： Wang, Juzhen Wang, Hanhong Wang, Wei Zha, Haoran Hangzhou Dianzi University School of Communication Engineering Hangzhou310018 China Binjiang Institute of Artificial Intelligence of Zhejiang University of Technology Hangzhou310052 China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China Harbin Engineering University College of Information and Communication Engineering Harbin150009 China

Specific Emitter Identification (SEI), based on the inevitable hardware imperfections of emitters, plays a crucial role in physical layer security, independent of upper-layer cryptographic methods. In recent years, SEI combined with deep learning has demonstrated exceptional performance and considerable potential. However, most SEI methods are designed for closed, independent identically distributed environments, which contrasts with real-world open scenarios. This discrepancy leads to significant security vulnerabilities when deploying models in practical applications. To address this challenge, we propose a novel Open-Set SEI (OS-SEI) framework, Outlier Exposure with Label Smoothing (OELS), which utilizes partial exposure to auxiliary anomalous data during the training phase and introduces specific loss functions to mitigate the open-set risk. By constructing smooth decision boundaries through label smoothing and applying thresholds to class confidence, our SEI framework demonstrates robust open-set authentication capabilities. Extensive experiments conducted on ADS-B and WiFi datasets show that the OELS method achieves outstanding open-set recognition performance, with F1 scores of 83.77% and 93.14% at an openness level of 0.10557. Furthermore, ablation experiments confirm the effectiveness and potential of our framework’s components. By increasing the diversity of auxiliary unknown data, we further improve performance in OS-SEI tasks. © 2014 IEEE.

关键词： Hardware security

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Fake News Detection Across Multiple Domains Using Fuzzy Association Rules 24th

Fake News Detection Across Multiple Domains Using Fuzzy Asso...

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24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Xu, Xiaofeng Zhang, Weisha Huang, Yuanyuan Lu, Hongyu Lu, Jiazhong School of Cybersecurity Xin Gu Industrial College Chengdu University of Information Technology Chengdu610225 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610225 China SUGON Industrial Control and Security Center Chengdu610225 China School of Foreign Languages University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9789819615247

The detection of fake news is not confined to a single domain, and due to domain transfer, the reliance on detection methods specific to a single domain becomes inadequate when dealing with multi-domain issues. When a multi-domain detection occurs, labels from one domain focus exclusively on the news characteristics of that particular domain, ignoring the possibility that part of the news may include functions from more than one domain. To address these challenges, we propose a multi-domain fake news detection model based on fuzzy rules, incorporating a fuzzy mechanism and an optimization module for fuzzy association rules. In this model, we first introduce a fuzzy mechanism that applies fuzzy processing to domains through neural networks, constructing fuzzy domain labels for each news domain. Subsequently, we incorporate fuzzy association rules to extract a broader range of sample features, thereby enhancing detection effectiveness. Experiments conducted on a fake news dataset demonstrate that our model achieves commendable detection performance with a relatively low training cost, reaching an F1 score of over 97.13% for sample detection. This model successfully overcomes the limitations of single-domain detection in fake news identification and improves the precision of feature extraction through fuzzy rules, showing superior performance in handling multi-domain fake news detection. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： fake news detection fuzzy rules multi-domain social media

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Load Balancing Routing Algorithm for LEO Satellite Networks Based on Ant Colony Optimization

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Internet technology Letters 2025年第3期8卷

作者： Zhi, Ruxin Wang, Jiahui Xu, Zhan Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China School of Information and Communication Engineering Beijing Information Science and Technology University Beijing China

To address the problem of the unbalanced load and optimize the traffic distribution of large-scale low earth orbit (LEO) satellite networks, this paper proposes a load-balancing routing algorithm for LEO satellite networks based on ant colony optimization. The algorithm establishes the global optimal initial path through the improved ant colony algorithm to bypass the network bottleneck, makes local adjustments to cope with burst traffic changes to avoid congestion, and optimizes the "inferior" paths through regular rerouting to improve the overall network performance. The results show that the algorithm performs well in terms of packet loss rate, throughput, and load balancing, which can effectively alleviate the link utilization imbalance problem and provide a more stable and efficient service for the satellite network. Among them, the packet loss rate is reduced by 7.8%, and the load distribution index is improved by 30%. © 2025 The Author(s). Internet technology Letters published by John Wiley & Sons Ltd.

关键词： Ant colony optimization

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Delayed interference-based broadband optical chaos generation in a mutual coupled RSOA and DFB system

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Optics Letters 2025年第10期50卷 3381-3384页

作者： Qian, Jiahao Jiang, Ning Li, Anran Zhang, Yiqun Xu, Bingjie Huang, Wei Qiu, Kun School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu 611731 China Tianfu Jiangxi Laboratory Chengdu 641419 China National Key Laboratory of Security Communication Chengdu 610041 China

In this Letter, a delayed interference (DI)-based chaos generation scheme in a mutually coupled system consisting of a reflective semiconductor optical amplifier (RSOA) and a distributed feedback (DFB) semiconductor laser is proposed. We experimentally demonstrate its capability of generating broadband chaos with a large effective bandwidth and a flat power spectrum, and the influences of relevant parameters on the system performance are thoroughly analyzed. Compared to the conventional optical feedback-based chaos generation schemes, the proposed system can simultaneously output two chaotic signals with enhanced bandwidth and high spectral flatness. Moreover, the time-delay signature (TDS) of chaotic signals generated by this configuration is also effectively suppressed. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Distributed feedback lasers Passive optical networks Random number generation Semiconductor lasers Semiconductor optical amplifiers Variable optical attenuators

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Correction to: An advanced reinforcement learning control method for quadruped robots in typical urban terrains (International Journal of Machine Learning and Cybernetics, (2024), 10.1007/s13042-024-02478-9)

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International Journal of Machine Learning and Cybernetics 2025年 1-2页

作者： Yan, Chi Wang, Ning Gao, Hongbo Wang, Xinmiao Tang, Chao Zhou, Lin Li, Yuehua Wang, Yue School of Information Science and Technology University of Science and Technology of China No. 96 Jinzhai Road Anhui Hefei230026 China School of Information and Security Chongqing College of Mobile Communication No. 36 Dengying Avenue Qijiang District Sichuan Chongqing401520 China Institute of Advanced Technology University of Science and Technology of China No. 5089 Wangjiang West Road Anhui Hefei230088 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Nanyang639798 Singapore Zhejiang Lab Kechuang Avenue Zhongtai Sub-District Zhejiang Hangzhou311121 China College of Control Science and Engineering Zhejiang University Zhejiang Hangzhou310027 China

In this article, the affiliation details for Authors "Ning Wang2, Hongbo Gao1,3,4, Yuehua Li5, Yue Wang6" were interchanged and it is corrected now. Incorrect affiliation: 2Institute of Advanced technology, University of science and technology of China, No. 5089 Wangjiang West Road, Hefei 230088, Anhui, China 3School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798 Nanyang, Singapore 4Zhejiang Lab, Kechuang Avenue, Zhongtai Sub-District, Hangzhou 311121, Zhejiang, China 5College of control science and Engineering, Zhejiang University, Hangzhou 310027, Zhejiang, China 6School of information and security, Chongqing College of Mobile communication, No. 36 Dengying Avenue, Qijiang District, Chongqing 401520, Sichuan, China Correct affiliation: 2School of information and security, Chongqing College of Mobile communication, No. 36 Dengying Avenue, Qijiang District, Chongqing 401520, Sichuan, China 3Institute of Advanced technology, University of science and technology of China, No. 5089 Wangjiang West Road, Hefei 230088, Anhui, China 4School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798 Nanyang, Singapore 5Zhejiang Lab, Kechuang Avenue, Zhongtai Sub-District, Hangzhou 311121, Zhejiang, China 6College of control science and Engineering, Zhejiang University, Hangzhou 310027, Zhejiang, China The original article has been corrected. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

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Synergistic Task-Offloading in 6g Edge Networks Based on Propagation Dynamics

SSRN

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SSRN 2025年

作者： Zhu, Chao Zhang, Yuexia Wang, Xinyi Zhu, Xuzhen The Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China The Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

In future 6G edge networks, Device-to-Device (D2D)-assisted Mobile Edge Computing (MEC) can fully utilize the idle resources of smart terminals and alleviate the burden on backhaul links. However, the limited idle resources of smart terminals and the over-reliance on D2D-assisted computation offloading may result in a large number of terminals experiencing task overload, which could lead to the risk of edge network paralysis. To address these issues, this paper establishes a Service-Auxiliary-Request-Healing (SARH) task-offloading propagation model based on propagation dynamics theory. This model describes the dynamic transmission process of offloaded tasks in 6G edge networks and constructs two linear threshold functions to characterize the differences in task processing capabilities between user terminals and edge servers. Furthermore, the proposed task-offloading propagation model is theoretically analyzed using edge compartment theory, and the propagation dynamics equations are established to derive the saddle point and critical conditions leading to task overload in a large number of user terminals, providing theoretical guidance for preventing network paralysis. Finally, simulation results show that the SARH model effectively describes the task-offloading propagation process in edge networks, and by controlling key factors such as the proportion of user terminals selecting D2D-assisted MEC synergistic task-offloading, network connectivity density, and network degree distribution heterogeneity, network paralysis can be avoided. © 2025, The Authors. All rights reserved.

关键词： Computation offloading

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Integrated communication and Learned Recognizer with Customized RIS Phases and Sensing Durations

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IEEE Transactions on communications 2025年

作者： Huang, Yixuan Yang, Jie Wen, Chao-Kai Jin, Shi Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education The Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China National Sun Yat-sen University Institute of Communications Engineering Kaohsiung80424 Taiwan Southeast University Frontiers Science Center for Mobile Information Communication and Security National Mobile Communications Research Laboratory Nanjing210096 China

Future wireless communication networks are expected to be smarter and more aware of their surroundings, enabling a wide range of context-aware applications. Reconfigurable intelligent surfaces (RISs) are set to play a critical role in supporting various sensing tasks, such as target recognition. However, current methods typically use RIS configurations optimized once and applied over fixed sensing durations, limiting their ability to adapt to different targets and reducing sensing accuracy. To overcome these limitations, this study proposes an advanced wireless communication system that multiplexes downlink signals for environmental sensing and introduces an intelligent recognizer powered by deep learning techniques. Specifically, we design a novel neural network based on the long short-term memory architecture and the physical channel model. This network iteratively captures and fuses information from previous measurements, adaptively customizing RIS phases to gather the most relevant information for the recognition task at subsequent moments. These configurations are dynamically adjusted according to scene, task, target, and quantization priors. Furthermore, the recognizer includes a decision-making module that dynamically allocates different sensing durations, determining whether to continue or terminate the sensing process based on the collected measurements. This approach maximizes resource utilization efficiency. Simulation results demonstrate that the proposed method significantly outperforms state-of-the-art techniques while minimizing the impact on communication performance, even when sensing and communication occur simultaneously. Part of the source code for this paper can be accessed at https://***/kiwi1944/CRISense. © 1972-2012 IEEE.

关键词： Long short-term memory

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Improving key rates by tighter information reconciliation leakage estimation for quantum key distribution

arXiv

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arXiv 2025年

作者： Mao, Hao-Kun Yang, Bo Qiao, Yu-Cheng Yan, Bing-Ze Zhao, Qiang Xu, Bing-Jie Li, Qiong School of Cyberspace Science Faculty of Computing Harbin Institute of Technology Harbin150080 China Guangxi Key Lab Cryptography and Information Security Guilin University of Electronic Technology Guangxi Guilin541004 China School of Information Engineering Zhejiang Ocean University Zhoushan316022 China Science and Technology on Security Communication Laboratory Institute of Southwestern Communication Chengdu610041 China

Previous research has aimed to precisely estimate information leakage to improve the secure key rate (SKR) and maximum transmission distance in quantum key distribution (QKD). However, existing methods repeatedly considerd the information of the multi-photon pulses known to Eve before and after information reconciliation, resulting in an overestimation of the leakage amount. We propose a novel approach that considers the quantum part’s effect on post-processing, providing a more accurate estimation of information reconciliation leakage to improve the SKR. Theoretical analysis shows that our method more accurately estimates the information reconciliation leakage, significantly improving the SKR at any distance as well as the maximum transmission distance. It is worth mentioning that previous studies treat information leakage of the error correction as Shannon bound Nh(e), and our method can estimate it more tightly. Simulation results for decoy-BB84 and measurement-device-independent (MDI) protocols using Cascade are consistent with the theoretical analysis. The farther the transmission distance, the greater the growth rate of SKR. When the error rate is 33%, compared with the original method, the SKR growth rate of decoy-BB84 at 100KM is 100.4%, and the transmission distance of MDI increases by 22KM. Copyright © 2025, The Authors. All rights reserved.

关键词： information leakage

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