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International Joint Conference on Neural networks (IJCNN)

作者： Runnan Tan Qingfeng Tan Haiyan Wang Yushun Xie Peng Zhang Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou China Department of New Networks PengCheng Laboratory Shenzhen China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen China The School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Anonymous networks play a crucial role in preserving information privacy, yet simultaneously spark technical conflicts and gamesmanship between their maintainers and regulatory authorities. To solve the above conflicts and economic losses in real networks, it is imminent to realize adversarial exercises in anonymous networks and validate new technologies and scenarios in the cyber range. It is well known that the two dominant types of anonymity networks are Tor and Invisible Internet Project (I2P). This paper establishes a cyber range based on I2P to realize a task-driven automated scenario construction technique. The proposed task-driven automated scenario construction technique can solve the problem of decoupling between business scenarios and I2P cyber range network infrastructure. Specifically, our approach allows users to upload models/executable code to extend flexibly and fine-grained control I2P nodes, protocols, and traffic behavior characteristics. Then it empowers users to define application scenarios as needed, enabling them to handle intricate business scenarios programmatically. Therefore, it further supports diverse adversarial exercises and the validation of new technologies and scenarios within the dark web.

关键词： Measurement Privacy Costs Protocols Dark Web Scalability Neural networks

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Logarithmic Identity-Based Ring Signature Over Lattices and Linkable Variant

SSRN

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SSRN 2024年

作者： Gao, Wen Fu, Tianyou Qin, Baodong Dong, Xiaoli Zhao, Zhen Liu, Momeng School of Cyberspace Security Xi’an University of Posts and Telecommunications Shaanxi Xi’an China School of Cyber Engineering Xi’dian University Shaanxi Xi’an China School of Computer Science Xi’an Polytechnic University Xi’an China State Key Laboratory of Integrated Services Networks Xidian University China

The ring signature is extensively utilized in a multitude of fields, including e-voting, cryptocurrency, and blockchain settings, etc. To make the ring signature able to cope with the challenges of quantum attacks, this paper proposes an effective identity-based ring signature (IBRS) from the lattice assumption by using logarithmic size OR proofs of group action. Our construction is proved to be anonymous and unforgeable in the random oracle model (ROM) under the hardness of Module Small Integer Solution (MSIS) assumption from lattices, which is a hot quantum-resistant cryptographic primitive. The anonymity makes ring signature possible for a signer to sign the same message twice or more without being detected by the verifier. This would bring repeated e-voting or double spending of the same amount of money in blockchain. Therefore, as an additional work, we give a linkable variant. Compared with existing IBRS schemes with linear sizes, the size of our scheme is relatively short and achieves logarithmic communication cost with its ring scale N. Our research data show that the signature size of our proposal has significant advantages over several existing schemes with an increase of N. When the ring scale N is set to be 32 (512, resp.), our scheme has a signature size of 96.90KB (99.52KB, resp.), while the previous scheme has a size at least 154.06KB (2695.74KB, resp.). © 2024, The Authors. All rights reserved.

关键词： Blockchain

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Semantic Feature Division Multiple Access for Digital Semantic Multiple Access Channels

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Shen, Bin Ma, Shuai Chen, Rui Wu, Youlong Li, Hang Shi, Guangming Li, Shiyin Al-Dhahir, Naofal China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Xidian University State Key Laboratory of Integrated Service Networks School of Telecommunications Engineering Shaanxi Xi'an710071 China ShanghaiTech University School of Information Science and Technology Shanghai201210 China Shenzhen Research Institute of Big Data Guangdong Shenzhen518172 China Xidian University School of Artificial Intelligence Shaanxi Xi'an710071 China Peng cheng Laboratory Shenzhen518066 China The University of Texas at Dallas Department of Electrical and Computer Engineering RichardsonTX75080 United States

To solve the multi-user semantic communication network capacity bottlenecks, this paper proposes a semantic feature domain multiple access (SFDMA) scheme. By extracting and encoding semantic features and jointly processing multi-user data, the scheme can realize the encoding and transmission of multi-user semantic information in the separated feature subspace. Based on this scheme, a semantic digital multiple access network model is proposed to perform multi-user inference tasks, and an efficient semantic encoding and decoding scheme is developed by using variational information bottleneck (VIB) theory to ensure both the orthogonality in the feature domain and the classification accuracy. Furthermore, a SFDMA model for image reconstruction is designed based on the Swin Transformer. The modified model also considers the reconstruction quality and orthogonality of semantic feature domain. In addition, we design an optimization target for multiple access to implement an adaptive power allocation method for multi-user semantic communications. Simulation results show that our proposed SFDMA scheme exhibits semantic feature domain orthogonality in different applications, and the adaptive power allocation method shows excellent performance in the classification task, and effectively guarantee the quality of service (QoS) of the semantic communications. © 2015 IEEE.

关键词： Image reconstruction

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Coherent stacking of 128 pulses amplified in the large nonlinear regime with pre-amplitude modulation

Coherent stacking of 128 pulses amplified in the large nonli...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Kangzhu Zhou Bowei Yang Zhigang Zhang Qian Li School of Electronic and Computer Engineering Peking University Shenzhen China State Key Laboratory of Advanced Optical Communication System and Networks School of Electronics Peking University Beijing China

We numerically demonstrate a coherent pulse stacking of 128 pulses amplified in the large nonlinear amplification regime.

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

We numerically demonstrate a coherent pulse stacking of 128 pulses amplified in the large nonlinear amplification regime.

关键词： Optical fiber amplifiers Stacking Modulation Lasers and electrooptics Electro-optic modulators Fiber lasers

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Robust Co-Optimization of Distribution Network Hardening and Mobile Resource Scheduling with Decision-Dependent Uncertainty

arXiv

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arXiv 2025年

作者： Ma, Donglai Cao, Xiaoyu Zeng, Bo Chen, Chen Zhai, Qiaozhu Jia, Qing-Shan Guan, Xiaohong School of Automation Science and Engineering The Ministry of Education Key Laboratory for Intelligent Networks and Network Security Xi’an Jiaotong University Shaanxi Xi’an710049 China Department of Industrial Engineering The Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA15106 United States School of Electrical Engineering Xi’an Jiaotong University Shaanxi Xi’an710049 China Center for Intelligent and Networked Systems Department of Automation Tsinghua University Beijing100084 China

This paper studies the robust co-planning of proactive network hardening and mobile hydrogen energy resources (MHERs) scheduling, which is to enhance the resilience of power distribution network (PDN) against the disastrous events. A decision-dependent robust optimization model is formulated with min − max resilience constraint and discrete recourse structure, which helps achieve the load survivability target considering endogenous uncertainties. Different from the traditional model with a fixed uncertainty set, we adopt a dynamic representation that explicitly captures the endogenous uncertainties of network contingency as well as the available hydrogen storage levels of MHERs, which induces a decision-dependent uncertainty (DDU) set. Also, the multi-period adaptive routing and energy scheduling of MHERs are modeled as a mixed-integer recourse problem for further decreasing the resilience cost. Then, a nested parametric column-and-constraint generation (N-PC&CG) algorithm is customized and developed to solve this challenging formulation. By leveraging the structural property of the DDU set as well as the combination of discrete recourse decisions and the corresponding extreme points, we derive a strengthened solution scheme with nontrivial enhancement strategies to realize efficient and exact computation. Numerical results on 14-bus test system and 56-bus real-world distribution network demonstrate the resilience benefits and economical feasibility of the proposed method under different damage severity levels. Moreover, the enhanced NPC&CG shows a superior solution capability to support prompt decisions for resilient planning with DDU models. Copyright © 2025, The Authors. All rights reserved.

关键词： Hardening

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Heart Disease Prediction Algorithm Based on Ensemble Learning 7

Heart Disease Prediction Algorithm Based on Ensemble Learnin...

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7th International Conference on Dependable Systems and Their Applications, DSA 2020

作者： Yuan, Ke Yang, Longwei Huang, Yabing Li, Zheng Henan University International Joint Research Laboratory for Cooperative Vehicular Networks of Henan School of Computer and Information Engineering China Henan University School of Computer and Information Engineering China

ISBN: (纸本)9780738124223

Nowadays, heart disease is one of the important causes of human deaths. According to statistics, deaths caused by heart disease account for about one-third of all deaths in the world. With further research, the use of machine learning to predict heart disease has become an essential method to prevent and treat heart disease. In recent years, machine learning based on big data analysis has been widely used in various software applications, but it has not been used on a large scale in disease prediction. In this article, we propose a new algorithm named hybrid gradient boosting decision tree with logistic regression (HGBDTLR) based on ensemble learning to improve the accuracy of machine learning in heart disease prediction. The actual results prove that the prediction accuracy of HGBDTLR algorithm can reach 91.8% in the Cleveland heart disease data set. © 2020 IEEE.

关键词： Forecasting

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A Blockchain-Enabled Secure and Decentralized ADS-B System for Intelligent Vehicles With Robust Authentication

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IEEE Transactions on Vehicular Technology 2025年

作者： Yao, Chong Zhang, Xuejun Liu, Yizhong Zhao, Boyu Tiwari, Prayag Kumar, Neeraj Beihang University State Key Laboratory of CNS/ATM the School of Electronic Information Engineering China Beihang University School of Cyber Science and Technology Beijing China Halmstad University School of Information Technology Sweden Thapar Institute of Engineering and Technology CSED Punjab Patiala India UEHS Poland Imam Abdulrahman Bin Faisal University Department of Networks and Communications the College of Computer Science and Information Technology Dammam Saudi Arabia

As the next-generation air traffic surveillance technology, the Automatic Dependent Surveillance-Broadcast (ADS-B) system plays a critical role in broadcast communication for intelligent vehicles such as unmanned aerial vehiclesand aircraft. However, the unauthenticated channels expose the ADS-B system to a high risk of attacks. Besides, the centralization of intelligent vehicles management center is susceptible to single point failures and performance bottlenecks. In this paper, we propose a robust and distributed intelligent vehicles management architecture leveraging blockchain technology to resolve security and performance issues lying in the registration, update, and revocation of intelligent vehicles' identity public keys. Then, we leverage certificate-less short signature (CLSS) to achieve the dynamic identity verification of ADS-B system participants while ensuring message integrity, non-repudiation, and compatibility with low-data-bit message packets. Furthermore, to enhance intelligent vehicles transaction process efficiency within the proposed architecture, we develop an Verifiable Random Function-based Byzantine Fault Tolerance protocol (VRBFT) combining threshold signatures. Finally, through a comprehensive security analysis and feasibility assessment, the results indicate that authentication requires less than 30 ms, block generation occurs within 200 ms, and the system exhibits high throughput and low latency. These findings demonstrate that our solution significantly enhances the security of the ADS-B system and offers a practical and promising approach for real-time, large-scale intelligent vehicle management. © 2025 IEEE.

关键词： Blockchain

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A Parallelizable Counterfactual Generation Method Based on Gradient Optimization

A Parallelizable Counterfactual Generation Method Based on G...

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Haorun Ding Xuesong Jiang Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Quan Cheng Laboratory Jinan China State Key Laboratory of High-end Server & Storage Technology Jinan China

Post-hoc explanations are important for people to understand the predictions of explanation models. One class of methods in post-hoc explanation is the generation of counterfactuals, where a hypothetical example is obtained by perturbing the inputs to show how one could obtain a different prediction from the decision model. Counter-factual explanations should satisfy several properties: One is that counterfactuals generated under specific scenarios and constraints should be feasible for users, i.e., they should accommodate different causal constraints. The other is that it is more desirable for users to have a wider variety of viable examples, i.e., counterfactual diversity. To this end, we propose a parallelizable method based on gradient optimization. We partition the input feasible domains, perform counterfactual generation independently for each feasible domain, and then parallelize the counterfactual generation process for each feasible domain. Experimental results show that our approach effectively improves the diversity, sparsity, and proximity of the generated counterfactual instances on the public datasets Adult-Income, Lending-Club, German-Credit, and COMPAS compared to other models.

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Fusing Bluetooth with Pedestrian Dead Reckoning: A Floor Plan-Assisted Positioning Approach

arXiv

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arXiv 2025年

作者： Pan, Wenxuan Yang, Yang Chen, Mingzhe Wei, Dong Guo, Caili Mao, Shiwen Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical and Computer Engineering the Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Wireless Engineering Research and Education Center Auburn University AuburnAL36849 United States

Floor plans can provide valuable prior information that helps enhance the accuracy of indoor positioning systems. However, existing research typically faces challenges in efficiently leveraging floor plan information and applying it to complex indoor layouts. To fully exploit information from floor plans for positioning, we propose a floor plan-assisted fusion positioning algorithm (FP-BP) using Bluetooth low energy (BLE) and pedestrian dead reckoning (PDR). In the considered system, a user holding a smartphone walks through a positioning area with BLE beacons installed on the ceiling, and can locate himself in real time. In particular, FP-BP consists of two phases. In the offline phase, FP-BP programmatically extracts map features from a stylized floor plan based on their binary masks, and constructs a mapping function to identify the corresponding map feature of any given position on the map. In the online phase, FP-BP continuously computes BLE positions and PDR results from BLE signals and smartphone sensors, where a novel grid-based maximum likelihood estimation (GML) algorithm is introduced to enhance BLE positioning. Then, a particle filter is used to fuse them and obtain an initial estimate. Finally, FP-BP performs post-position correction to obtain the final position based on its specific map feature. Experimental results show that FP-BP can achieve a real-time mean positioning accuracy of 1.19 m, representing an improvement of over 28% compared to existing floor plan-fused baseline algorithms. Copyright © 2025, The Authors. All rights reserved.

关键词： Photomapping

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Joint Radio Resource Allocation and Control for Resource-Constrained Vehicle Platooning

Joint Radio Resource Allocation and Control for Resource-Con...

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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Dayue Zhang Nan Cheng Ruijin Sun Feng Lyu Yilong Hui Changle Li School of Telecommunications Engineering Xidian University Xi'an China School of Computer Science and Engineering Central South University Changsha China State Key Laboratory of Integrated Services Networks Xidian University Xi'an China

ISBN: (纸本)9781665435413

Vehicle platooning is an effective way to improve the efficiency and safety of transportation systems, in which a group of vehicles maintains a moving pattern by minimizing the tracking error of each vehicle. In this paper, a joint optimization of radio resource allocation for kinetic status information transmission and platoon control is considered under resource-constrained conditions to maintain the targeted inter-vehicle spacing. The formulated problem is approximately solved by the decomposition method, where the radio resource allocation and the platoon control are considered alternatively in two stages. In the first stage, a tracking error based scheduling strategy is presented for radio resource allocation. In the second stage, the control inputs of each vehicle are optimized based on the model predictive control (MPC). Simulation results show that the proposed scheme can achieve the objective of platoon control while having a low tracking error compared with other scheduling strategies.

关键词： Target tracking Simulation Transportation Information processing Kinetic theory Safety Resource management

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