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Photonic Sensors 2024年第1期14卷 85-98页

作者： Muwen LIANG Yabin ZHAO Yaping LUO Bin DU Wei HU Bing LIU Xihui MU Zhaoyang TONG department of Investigation People's Public Security University of ChinaBejing 100038China State Key Laboratory of NBC Protection for Civilian Beijing 102205China

Latent fingerprints(LFPs)at the crime scene are served as important clues to locate the trajectory of criminal behavior and portray the characteristics of the ***,visualizing LFPs is of considerable *** this work,the europium metal-organic framework(Eu-MOF)sensor was successfully constructed for sensitive detection of gallic acid(3,4,5-trihydroxybenzoic acid,GA)and visualization of the sweat *** boric-acid-modified Eu-MOF was prepared by using the simple one-pot solvothermal method using Eu as the metal i ion center and 3,5-dicarboxybenzeneboronic acid(BBDC)as the organic *** sensor showed desirable photoluminescent performance through the chelating of BBDC with Eu3+.The sensor exhibited the satisfactory linear relationship to GA in the range of 1 nM to 20 nM with a low detection limit of 0.34 nM under the optimized *** prepared sensor with ideal selectivity to GA was successfully applied for visualizing LFPs on porous substrates with the high contrast and superior *** the good performance of the sensor,all fingerprint images obtained from 1200 samples presented clear friction ridges and met the identification ***,the sensor had less impact on the subsequent deoxyribonucleic acid(DNA)detection,displaying a promising perspective for applications in extracting physical evidence of site investigation.

关键词： Europium metal-organic framework(Eu-MOF) photoluminescence 3,4,5-trihydroxybenzoic latent fingerprints(LFPs)development

Tuning Second Chern Number in a Four-Dimensional Topological Insulator by High-Frequency Time-Periodic Driving

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Chinese Physics Letters 2024年第4期41卷 77-89页

作者：刘峥嵘陈锐周斌 department of Physics Hubei UniversityWuhan 430062China Key Laboratory of Intelligent Sensing System and security of Ministry of Education Hubei UniversityWuhan 430062China

Floquet engineering has attracted considerable attention as a promising approach for tuning topological phase *** investigate the effects of high-frequency time-periodic driving in a four-dimensional(4D)topological insulator,focusing on topological phase transitions at the off-resonant quasienergy *** 4D topological insulator hosts gapless three-dimensional boundary states,characterized by the second Chern number C_(2).We demonstrate that the second Chern number of 4D topological insulators can be modulated by tuning the amplitude of time-periodic *** includes transitions from a topological phase with C_(2)=±3 to another topological phase with C_(2)=±1,or to a topological phase with an even second Chern number C_(2)=±2,which is absent in the 4D static ***,the approximation theory in the high-frequency limit further confirms the numerical conclusions.

关键词： topological transitions Periodic

Suboptimal Feature Selection Techniques for Effective Malicious Traffic Detection on Lightweight Devices

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1669-1687页

作者： So-Eun Jeon Ye-Sol Oh Yeon-Ji Lee Il-Gu Lee department of Future Convergence Technology Engineering Sungshin Women’s UniversitySeoul02844Korea department of Convergence security Engineering SungshinWomen’s UniversitySeoul02844Korea

With the advancement of wireless network technology,vast amounts of traffic have been generated,and malicious traffic attacks that threaten the network environment are becoming increasingly *** signature-based detection methods,static analysis,and dynamic analysis techniques have been previously explored for malicious traffic detection,they have limitations in identifying diversified malware traffic *** research has been focused on the application of machine learning to detect these ***,applying machine learning to lightweight devices like IoT devices is challenging because of the high computational demands and complexity involved in the learning *** this study,we examined methods for effectively utilizing machine learning-based malicious traffic detection approaches for lightweight *** introduced the suboptimal feature selection model(SFSM),a feature selection technique designed to reduce complexity while maintaining the effectiveness of malicious traffic *** performance was evaluated on various malicious traffic,benign,exploits,and generic,using the UNSW-NB15 dataset and SFSM sub-optimized hyperparameters for feature selection and narrowed the search scope to encompass all *** improved learning performance while minimizing complexity by considering feature selection and exhaustive search as two steps,a problem not considered in conventional *** experimental results showed that the detection accuracy was improved by approximately 20%compared to the random model,and the reduction in accuracy compared to the greedy model,which performs an exhaustive search on all features,was kept within 6%.Additionally,latency and complexity were reduced by approximately 96%and 99.78%,respectively,compared to the greedy *** study demonstrates that malicious traffic can be effectively detected even in lightweight device *** verified the possibility of detecting various attack

关键词： Feature selection lightweight device machine learning Internet of Things malicious traffic

A Trust Evaluation Mechanism Based on Autoencoder Clustering Algorithm for Edge Device Access of IoT

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Computers, Materials & Continua 2024年第2期78卷 1881-1895页

作者： Xiao Feng Zheng Yuan Cyber security Academy Beijing University of Posts and TelecommunicationsBeijing100876China department of Cyberspace security Beijing Electronic Science and Technology InstituteBeijing100070China State Grid Info-Telecom Great Power Science and Technology Co. Ltd.Beijing102211China

First,we propose a cross-domain authentication architecture based on trust evaluation mechanism,including registration,certificate issuance,and cross-domain authentication processes.A direct trust evaluation mechanism based on the time decay factor is proposed,taking into account the influence of historical interaction *** weight the time attenuation factor to each historical interaction record for updating and got the new historical record *** refer to the beta distribution to enhance the flexibility and adaptability of the direct trust assessment model to better capture time trends in the historical *** we propose an autoencoder-based trust clustering *** perform feature extraction based on *** leibler(KL)divergence is used to calculate the reconstruction *** constructing a convolutional autoencoder,we introduce convolutional neural networks to improve training efficiency and introduce sparse constraints into the hidden layer of the *** sparse penalty term in the loss function measures the difference through the KL *** clustering is performed based on the density based spatial clustering of applications with noise(DBSCAN)clustering *** the clustering process,edge nodes have a variety of trustworthy attribute *** assign different attribute weights according to the relative importance of each attribute in the clustering process,and a larger weight means that the attribute occupies a greater weight in the calculation of ***,we introduced adaptive weights to calculate comprehensive trust *** experiments prove that our trust evaluation mechanism has excellent reliability and accuracy.

关键词： Cross-domain authentication trust evaluation autoencoder

Differentially Private Support Vector Machines with Knowledge Aggregation

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Computers, Materials & Continua 2024年第3期78卷 3891-3907页

作者： Teng Wang Yao Zhang Jiangguo Liang Shuai Wang Shuanggen Liu School of Cyberspace security Xi’an University of Posts and TelecommunicationsXi’an710121China

With the widespread data collection and processing,privacy-preserving machine learning has become increasingly important in addressing privacy risks related to *** vector machine(SVM)is one of the most elementary learning models of machine *** issues surrounding SVM classifier training have attracted increasing *** this paper,we investigate Differential Privacy-compliant Federated Machine Learning with Dimensionality Reduction,called FedDPDR-DPML,which greatly improves data utility while providing strong privacy *** in distributed learning scenarios,multiple participants usually hold unbalanced or small amounts of ***,FedDPDR-DPML enables multiple participants to collaboratively learn a global model based on weighted model averaging and knowledge aggregation and then the server distributes the global model to each participant to improve local data *** at high-dimensional data,we adopt differential privacy in both the principal component analysis(PCA)-based dimensionality reduction phase and SVM classifiers training phase,which improves model accuracy while achieving strict differential privacy ***,we train Differential privacy(DP)-compliant SVM classifiers by adding noise to the objective function itself,thus leading to better data *** experiments on three high-dimensional datasets demonstrate that FedDPDR-DPML can achieve high accuracy while ensuring strong privacy protection.

关键词： Differential privacy support vector machine knowledge aggregation data utility

Novel Rifle Number Recognition Based on Improved YOLO in Military Environment

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Computers, Materials & Continua 2024年第1期78卷 249-263页

作者： Hyun Kwon Sanghyun Lee department of Artificial Intelligence and Data Science Korea Military AcademySeoulKorea Graduate School of Information security Korea Advanced Institute of Science and TechnologyDaejeonKorea

Deep neural networks perform well in image recognition,object recognition,pattern analysis,and speech *** military applications,deep neural networks can detect equipment and recognize *** military equipment,it is necessary to detect and recognize rifle management,which is an important piece of equipment,using deep neural *** have been no previous studies on the detection of real rifle numbers using real rifle image *** this study,we propose a method for detecting and recognizing rifle numbers when rifle image data are *** proposed method was designed to improve the recognition rate of a specific dataset using data fusion and transfer *** the proposed method,real rifle images and existing digit images are fusedas trainingdata,andthe final layer is transferredto theYolov5 *** detectionand recognition performance of rifle numbers was improved and analyzed using rifle image and numerical *** used actual rifle image data(K-2 rifle)and numeric image datasets,as an experimental *** was used as the machine learning *** results show that the proposed method maintains 84.42% accuracy,73.54% precision,81.81% recall,and 77.46% F1-score in detecting and recognizing rifle *** proposed method is effective in detecting rifle numbers.

关键词： Machine learning deep neural network rifle number recognition detection

The Transfer and Change of Paints in a Hit-and-run Motor Vehicle Accident

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Journal of Forensic Science and Medicine 2024年第1期10卷 24-27页

作者： Can Hu Jun Zhu Hongcheng Mei Hongling Guo Ping Wang Yajun Li Trace Evidence department Institute of Forensic ScienceMinistry of Public SecurityXichengBeijingChina

This work investigated transfer and change of paint evidences in a case of *** kinds of attachments were found on the clothes of the victim and they were initially considered paint fragments from the vehicle causing the *** spectroscopy(IR),scanning electron microscope-energy dispersive spectrometer,and Microspectrophotometry were applied for examination of paints and clothing *** was detected in one of the attachments and in the clothing fibers of the victim by IR.A traffic accident simulation experiment was designed and conducted to research whether the polyester attachments come from suspected vehicle paints or victim’s clothing *** results showed that a melt mixture of transferred paints and clothing fiber was formed after a violent *** the amount of transferred paints was too low to be detectable in the mixture,the components detected by IR were mainly from clothing ***,we inferred that only one kind of attachment and paint fragments existed on the clothes of the victim,and the polyester attachments cannot be used to indicate the composition of suspected vehicle *** fibers and paints are both common trace evidence in traffic accident cases,and more attention should be paid to the examination of transferred paints on clothing fibers.

关键词： Clothing fibers hit‑and‑run traffic accident infrared spectroscopy paints trace evidence transfer

Blockchain-Assisted Unsupervised Learning Method for Crowdsourcing Reputation Management

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2297-2314页

作者： Tianyu Wang Kongyang Chen department of Cyberspace security Guangzhou UniversityGuangzhou51006China Institute of Artificial Intelligence Guangzhou UniversityGuangzhou51006China Center of Young Scholars Pazhou LabGuangzhou510335China

Crowdsourcing holds broad applications in information acquisition and dissemination,yet encounters challenges pertaining to data quality assessment and user reputation *** mechanisms stand as crucial solutions for appraising and updating participant reputation scores,thereby elevating the quality and dependability of crowdsourced ***,these mechanisms face several challenges in traditional crowdsourcing systems:1)platform security lacks robust guarantees and may be susceptible to attacks;2)there exists a potential for large-scale privacy breaches;and 3)incentive mechanisms relying on reputation scores may encounter issues as reputation updates hinge on task demander evaluations,occasionally lacking a dedicated reputation update *** paper introduces a reputation update scheme tailored for crowdsourcing,with a focus on proficiently overseeing participant reputations and alleviating the impact of malicious activities on the sensing ***,the reputation update scheme is determined by an Empirical Cumulative distribution-based Outlier Detection method(ECOD).Our scheme embraces a blockchain-based crowdsourcing framework utilizing a homomorphic encryption method to ensure data transparency and *** of user reputation scores relies on their behavioral history,actively discouraging undesirable ***,we introduce a dynamic weight incentive mechanism that mirrors alterations in participant reputation,enabling the system to allocate incentives based on user behavior and *** scheme undergoes evaluation on 11 datasets,revealing substantial enhancements in data credibility for crowdsourcing systems and a reduction in the influence of malicious *** research not only presents a practical solution for crowdsourcing reputation management but also offers valuable insights for future research and applications,holding promise for fostering more reliable and high-quality data collection in

关键词： Crowdsourcing reputation management blockchain

MarkNeRF:Watermarking for Neural Radiance Field

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Computers, Materials & Continua 2024年第7期80卷 1235-1250页

作者： Lifeng Chen Jia Liu Wenquan Sun Weina Dong Xiaozhong Pan Cryptographic Engineering department Institute of Cryptographic EngineeringEngineering University of PAPXi’an710086China Key Laboratory of Network and Information security of PAP Xi’an710086China

This paper presents a novel watermarking scheme designed to address the copyright protection challenges encountered with Neural radiation field(NeRF)*** employ an embedding network to integrate the watermark into the images within the training ***,theNeRFmodel is utilized for *** copyright verification,a secret image is generated by inputting a confidential viewpoint into *** this basis,design an extraction network to extract embedded watermark images fromconfidential *** the event of suspicion regarding the unauthorized usage of NeRF in a black-box scenario,the verifier can extract the watermark from the confidential viewpoint to authenticate the model’s *** experimental results demonstrate not only the production of visually appealing watermarks but also robust resistance against various types of noise attacks,thereby substantiating the effectiveness of our approach in safeguarding NeRF.

关键词： Neural radiation field 3D watermark robustness black box

QBIoT:A Quantum Blockchain Framework for IoT with an Improved Proof-of-Authority Consensus Algorithm and a Public-Key Quantum Signature

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Computers, Materials & Continua 2024年第7期80卷 1727-1751页

作者： Ang Liu Qing Zhang Shengwei Xu Huamin Feng Xiu-bo Chen Wen Liu Network and Information Management Division Beijing Electronic Science and Technology InstituteBeijing100070China department of Cyberspace security Beijing Electronic Science and Technology InstituteBeijing100070China Information security Institute Beijing Electronic Science and Technology InstituteBeijing100070China General Office Beijing Electronic Science and Technology InstituteBeijing100070China Information security Center State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China

The Internet of Things(IoT)is a network system that connects physical devices through the Internet,allowing them to ***,IoT has become an integral part of our lives,offering convenience and smart ***,the growing number of IoT devices has brought about a corresponding increase in cybersecurity threats,such as device vulnerabilities,data privacy concerns,and network *** blockchain technology with IoT has proven to be a promising approach to enhance IoT ***,the emergence of quantum computing poses a significant challenge to the security of traditional classical cryptography used in blockchain,potentially exposing it to quantum *** support the growth of the IoT industry,mitigate quantum threats,and safeguard IoT data,this study proposes a robust blockchain solution for IoT that incorporates both classical and post-quantum security ***,we present the Quantum-Enhanced Blockchain Architecture for IoT(QBIoT)to ensure secure data sharing and integrity ***,we propose an improved Proof of Authority consensus algorithm called“Proof of Authority with Random Election”(PoARE),implemented within QBIoT for leader selection and new block ***,we develop a publickey quantum signature protocol for transaction verification in the ***,a comprehensive security analysis of QBIoT demonstrates its resilience against cyber threats from both classical and quantum *** summary,this research introduces an innovative quantum-enhanced blockchain solution to address quantum security concernswithin the realmof *** proposedQBIoT framework contributes to the ongoing development of quantum blockchain technology and offers valuable insights for future research on IoT security.

关键词： IoT quantum blockchain public-key quantum signature quantum hash function