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Fair Efficiency Comparisons of Decoy-state Quantum key Distribution Protocols

Chinese Journal of Electronics 2018年第2期27卷 241-249页

作者： LI Hongxin GAO Ming YAN Xueping YAN Bao HAN Yu SHAN Ling MA Zhi Information Engineering University State Key Laboratory of Mathematical Engineering and Advanced Computing College of Animal Science and Technology Henan University of Science and Technology

Taking the schemes based on different formulas of secure key rate as examples, we give a fair comparison between typical protocols under Universal composable(UC) security frame. Through analyzing the relationship of security parameters in post-processing stage and final secure key rate, we achieve the unified quantification between protocols based on Gottesman-Lo-L¨utkenhausPreskill(GLLP) formula and the ones under UC *** on the above research, the impact of different sending lengths and secure parameters on secure key rate is investigated. Besides, we analyze the conditions of fair comparison, and for the first time we give a fair comparison between the protocols based on GLLP formula and smooth entropy. By typical efficiency comparisons, we summarize the way for improving secure key rate in the light intensity choice and the single bit error rate estimation method.

关键词： Quantum key distribution(QKD) Finite-key Universal composable(UC) Fair comparison

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NOMANet: A Graph Neural Network Enabled Power Allocation Scheme for NOMA

arXiv

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arXiv 2025年

作者： Hou, Yipu Lu, Yang Chen, Wei Ai, Bo Niyato, Dusit Ding, Zhiguo State Key Laboratory of Advanced Rail Autonomous Operation China School of Computer Science and Technology Beijing Jiaotong University Beijing100044 China School of Electronics and Information Engineering Beijing Jiaotong University Beijing100044 China College of Computing and Data Science Nanyang Technological University 639798 Singapore Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi127788 United Arab Emirates

This paper proposes a graph neural network (GNN) enabled power allocation scheme for non-orthogonal multiple access (NOMA) networks. In particular, a downlink scenario with one base station serving multiple users over several subchannels is considered, where the number of subchannels is less than the number of users, and thus, some users have to share a subchannel via NOMA. Our goal is to maximize the system energy efficiency subject to the rate requirement of each user and the overall budget. We propose a deep learning based approach termed NOMA net (NOMANet) to address the considered problem. Particularly, NOMANet is GNN-based, which maps channel state information to the desired power allocation scheme for all subchannels. The multi-head attention and the residual/dense connection are adopted to enhance the feature extraction. The output of NOMANet is guaranteed to be feasible via the customized activation function and the penalty method. Numerical results show that NOMANet trained unsupervised achieves performance close to that of the successive convex approximation method but with a faster inference speed by about 700 times. Besides, NOMANet is featured by its scalability to both users and subchannels. © 2025, CC BY.

关键词： Channel state information

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Continual Reinforcement Learning for Digital Twin Synchronization Optimization

arXiv

引用

arXiv 2025年

作者： Tong, Haonan Chen, Mingzhe Zhao, Jun Hu, Ye Yang, Zhaohui Liu, Yuchen Yin, Changchuan The Beijing Key Laboratory of Network System Architecture and Convergence The Beijing Advanced Information Network Laboratory Beijing University of Posts and Telecommunications Beijing China Singapore The Department of Electrical and Computer Engineering Frost Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States The Department of Industrial and Systems Engineering University of Miami Coral GablesFL33146 United States The College of Information Science and Electronic Engineering Zhejiang University Zhejiang Hangzhou310027 China The Department of Computer Science North Carolina State University RaleighNC27695 United States The Beijing Key Laboratory of Network System Architecture and Convergence China The Beijing Advanced Information Network Laboratory Beijing University of Posts and Telecommunications Beijing100876 China

This article investigates the adaptive resource allocation scheme for digital twin (DT) synchronization optimization over dynamic wireless networks. In our considered model, a base station (BS) continuously collects factory physical object state data from wireless devices to build a real-time virtual DT system for factory event analysis. Due to continuous data transmission, maintaining DT synchronization must use extensive wireless resources. To address this issue, a subset of devices is selected to transmit their sensing data, and resource block (RB) allocation is optimized. This problem is formulated as a constrained Markov process (CMDP) problem that minimizes the long-term mismatch between the physical and virtual systems. To solve this CMDP, we first transform the problem into a dual problem that refines RB constraint impacts on device scheduling strategies. We then propose a continual reinforcement learning (CRL) algorithm to solve the dual problem. The CRL algorithm learns a stable policy across historical experiences for quick adaptation to dynamics in physical states and network capacity. Simulation results show that the CRL can adapt quickly to network capacity changes and reduce normalized root mean square error (NRMSE) between physical and virtual states by up to 55.2%, using the same RB number as traditional methods. © 2025, CC BY-NC-SA.

关键词： Markov processes

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AFDM-Enabled Integrated Sensing and Communication: Theoretical Framework and Pilot Design

arXiv

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arXiv 2025年

作者： Zhang, Fan Wang, Zhaocheng Mao, Tianqi Jiao, Tianyu Zhuo, Yinxiao Wen, Miaowen Xiang, Wei Chen, Sheng Karagiannidis, George K. Department of Electronic Engineering Tsinghua University Beijing100084 China State Key Laboratory of CNS/ATM Beijing Institute of Technology Beijing100081 China Zhuhai519088 China School of Electronic and Information Engineering South China University of Technology Guangzhou China School of Computing Engineering and Mathematical Sciences La Trobe University MelbourneVIC3086 Australia School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Greece

The integrated sensing and communication (ISAC) has been envisioned as one representative usage scenario of sixth-generation (6G) network. However, the unprecedented characteristics of 6G, especially the doubly dispersive channel, make classical ISAC waveforms rather challenging to guarantee a desirable performance level. The recently proposed affine frequency division multiplexing (AFDM) can attain full diversity even under doubly dispersive effects, thus becoming a competitive candidate for next-generation ISAC waveforms. Relevant investigations are still at an early stage, which involve only straightforward design lacking explicit theoretical analysis. This paper provides an in-depth investigation on AFDM waveform design for ISAC applications. Specifically, the closed-form Crámer-Rao bounds of target detection for AFDM are derived, followed by a demonstration on its merits over existing counterparts. Furthermore, we formulate the ambiguity function of the pilot-assisted AFDM waveform for the first time, revealing conditions for stable sensing performance. To further enhance both the communication and sensing performance of the AFDM waveform, we propose a novel pilot design by exploiting the characteristics of AFDM signals. The proposed design is analytically validated to be capable of optimizing the ambiguity function property and channel estimation accuracy simultaneously as well as overcoming the sensing and channel estimation range limitation originated from the pilot spacing. Numerical results have verified the superiority of the proposed pilot design in terms of dual-functional performance. Copyright © 2025, The Authors. All rights reserved.

关键词： Cramer-Rao bounds

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Research on Fuzzing Technology for JavaScript Engines 21

Research on Fuzzing Technology for JavaScript Engines

引用

5th International Conference on Computer Science and Application engineering, CSAE 2021

作者： Tian, Ye Qin, Xiaojun Gan, Shuitao State Key Laboratory of Mathematical Engineering and Advanced Computing Zheng zhou Wuxi China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China

ISBN: (纸本)9781450389853

JavaScript engine is the core component of web browsers, whose security issues are one of the critical aspects of the overall Web Eco-Security. Fuzzing technology, as an efficient software testing approach, has been widely applied to detecting vulnerabilities in different JavaScript engines, which is a security research hotspot at present. Based on systematical dissection of existing fuzzing methods, this paper reviews the development and technical ideas of JavaScript Engine Fuzzing combined with taxonomy, proposes a general framework of JavaScript Engine Fuzzing and analyzes the key techniques involved. Finally, we discuss the core issues that restrict efficiency in current research and present an outlook on the future trends of JavaScript Engine Fuzzing.. © 2021 Association for computing Machinery. All rights reserved.

关键词： Engines

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Vulnerability model and attack path prediction of the UEFI firmware platform based on risk propagation 11

Vulnerability model and attack path prediction of the UEFI f...

引用

2021 11th International Workshop on Computer Science and engineering, WCSE 2021

作者： Jiao, Weihua Li, Qingbao Chen, Zhifeng Cao, Fei State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9789811817915

Targeted at the situation of rampant attack on UEFI Platform Firmware, this paper systematically analyzes the Security mechanisms of UEFI platform firmware. Then the vulnerability factors of UEFI firmware are described by modeling language, and a vulnerability model of UEFI firmware platform based on risk propagation (VMURP) is proposed. This paper introduces an improved PageRank algorithm to this model to reduce the influence of subjective factors which influences the accuracy of model. Based on VMURP model, an innovative method is proposed which using security configuration vector and attack vector to evaluate attack paths. Then, we use this method and VMURP to predict the most possible attack path of specific UEFI firmware platform. Finally, verify the rationality of the model and the validity of the prediction by experimental analysis. This study is helpful to quickly evaluate the vulnerability of UEFI firmware platform and predict possible attacks, gives platform managers more targeted guidance and suggestions to strengthen the security mechanisms. © 2021 11th International Workshop on Computer Science and engineering, WCSE 2021. All Rights Reserved.

关键词： Forecasting

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APU-D* Lite: Attack Planning under Uncertainty Based on D* Lite

引用

Computers, Materials & Continua 2020年第11期65卷 1795-1807页

作者： Tairan Hu Tianyang Zhou Yichao Zang Qingxian Wang Hang Li State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001China School of Electrical Engineering and Telecommunications UNSW KensingtonNSW 2033Australia

With serious cybersecurity situations and frequent network attacks,the demands for automated pentests continue to increase,and the key issue lies in attack *** the limited viewpoint of the attacker,attack planning under uncertainty is more suitable and practical for pentesting than is the traditional planning approach,but it also poses some *** address the efficiency problem in uncertainty planning,we propose the APU-D*Lite algorithm in this ***,the pentest framework is mapped to the planning problem with the Planning Domain Definition Language(PDDL).Next,we develop the pentest information graph to organize network information and assess relevant exploitation actions,which helps to simplify the problem ***,the APU-D*Lite algorithm is introduced based on the idea of incremental heuristic *** method plans for both hosts and actions,which meets the requirements of *** the pentest information graph as the input,the output is an alternating host and action *** experiments,we use the attack success rate to represent the uncertainty level of the *** result shows that APU-D*Lite displays better reliability and efficiency than classical planning algorithms at different attack success rates.

关键词： Attack planning under uncertainty automated pentest APU-D*Lite algorithm incremental heuristic search

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引用

2020 International Conference on Computer Vision, Image and Deep Learning, CVIDL 2020

作者： Sun, Wenjie Shan, Zheng Liu, Fudong Qiao, Meng Gui, Hairen Li, Xingwei State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (数字)9781728194813

ISBN: (纸本)9781728194813

Graph matching has a wide range of applications. However, graph matching faces two challenges: high computational complexity and loss information of graph embedded. In order to solve these two problems and correctly identify the similarity between two function control flow graphs, we propose a binary function similarity comparison method based on Graph Mover's Distance. The model takes two graphs as input, and first learns the spatial structure of the nodes in the graph based on the graph attention neural network to form the node embedding. Then we use the sum of the distance between the two sets of node embeddings to represent the distance between the graphs as the graph similarity index. We conduct experiments on the control flow graph of the program and prove the effectiveness of the method. © 2020 IEEE.

关键词： Embeddings

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A Patch Analysis Method Based on Multi-firmware Comparison 2021

A Patch Analysis Method Based on Multi-firmware Comparison

引用

2021 International Symposium on Electrical, Electronics and Information engineering, ISEEIE 2021

作者： Xiao, Ruiqing Zhu, Yuefei Hu, Anxiang Zhu, Xiaoya Liu, Shengli State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781450389839

A major user need is the completion of security audits by locating vulnerability functions using vulnerability information published by firmware manufacturers. However, it is difficult to manually analyze the relatively large number of patch functions involved in firmware updates. A patch analysis method based on multi-firmware comparison is presented in this study. This method narrows the search for suspected patch functions for vulnerability based on the similarities and differences between different firmware series involved in the vulnerability. Suspected patch functions in multiple firmware programs are first located and filtered based on intervals. Finally, a prototype system is implemented. The filtering results for the prototype system are used to manually locate two one-day vulnerabilities. The experimental results demonstrate that the two methods proposed in this study, namely, patch function location in multiple firmware programs and interval-based patch function filtering, effectively narrow the search for suspected patch functions and reduce the difficulty of manual analysis. © 2021 ACM.

关键词： Firmware

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A Survey on Knowledge Graph Representation Learning with Text Information 3

A Survey on Knowledge Graph Representation Learning with Tex...

引用

3rd World Symposium on Software engineering, WSSE 2021

作者： Wang, Ling Lu, Jicang Zhou, Gang State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781450384094

Knowledge graph representation learning provides a lot of help for subsequent tasks such as knowledge graph completion, information retrieval, and intelligent question answering. By representing the knowledge graph as low-dimensional dense vectors, these tasks can improve efficiency significantly. However, limited by the sparseness and huge scale of the actual structure, representation learning only from a structural perspective can no longer meet the research needs. To improve the performance, researchers introduced auxiliary information into representation learning. This paper focuses on models using text as auxiliary information, dividing all text-combined models into two categories: Closed-world assumption models and Open-world assumption models. The former is limited by the model's demand for the structural representation of the graph itself, and can only predict the entities and relationships that already exist in the knowledge graph. The latter can handle entities that have not previously been seen during model training, and connect brand-new entities to the knowledge graph, which is more in line with the dynamic trend of the knowledge graph in real world. Open-world assumption models can be further subdivided into multiple types according different joint functions, such as alignment function, fusion function, score function and transformation function. This paper summarizes existing methods in detail and looks forward to future possible research directions. © 2021 ACM.

关键词： Knowledge graph

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