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Enhanced Privacy-Preserving WiFi Fingerprint Localization from CL Encryption

Chinese Journal of Electronics 2024年第6期33卷 1435-1446页

作者： Zhiwei WANG Qiuchi ZHU Zhenqi ZHANG School of Computer Nanjing University of Posts and Telecommunications State Key Laboratory of Public Big Data Guizhou University Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu University of Information Engineering Key Laboratory of Computational Science and Application of Hainan Province Hainan Normal University

The WiFi fingerprint-based localization method is considered one of the most popular techniques for indoor localization. In INFOCOM'14, Li et al. proposed a wireless fidelity(WiFi) fingerprint localization system based on Paillier encryption, which is claimed to protect both client C 's location privacy and service provider S's database privacy. However, Yang et al. presented a practical data privacy attack in INFOCOM'18, which allows a polynomial time attacker to obtain S's database. We propose a novel WiFi fingerprint localization system based on CastagnosLaguillaumie(CL) encryption, which has a trustless setup and is efficient due to the excellent properties of CL encryption. To prevent Yang et al.'s attack, the system requires that S selects only the locations from its database that can receive the nonzero signals from all the available access points in C 's nonzero fingerprint in order to determine C's location. security analysis shows that our scheme is secure under Li et al.'s threat model. Furthermore, to enhance the security level of privacy-preserving WiFi fingerprint localization scheme based on CL encryption, we propose a secure and efficient zero-knowledge proof protocol for the discrete logarithm relations in C's encrypted localization queries.

关键词： Location awareness Threat modeling Data privacy Protocols Databases Fingerprint recognition Trustless services Encryption Servers Wireless fidelity

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IMCSCL: Image-Based Malware Classification using Self-Supervised and Contrastive Learning 23

IMCSCL: Image-Based Malware Classification using Self-Superv...

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23rd IEEE International Conference on Software Quality, Reliability, and security, QRS 2023

作者： Jia, Yetao Meng, Yangyang Zhuang, Honglin National Key Laboratory of Science and Technology on Information System Security Beijing China

ISBN: (纸本)9798350319583

The use of malware for illicit cyber activities, including network attacks and information theft, poses a severe threat to cybersecurity. In comparison to traditional malware detection methods based on signature and heuristics, machine learning and deep learning-based malware detection methods demonstrate superior generalization ability. However, existing research still faces challenges such as reliance on relatively single malware features, inadequate ability to describe malware features, and overdependence on labeled data. In this paper, we propose an image-based malware classification method using self-supervised and contrastive learning, named IMCSCL. We visualize malware using opcode semantic features, and then detect malware using a contrastive learning method with improved feature encoder network. Experimental results demonstrate that IMCSCL achieves higher detection accuracy compared to supervised malware detection methods, achieving 98.85% accuracy on the Microsoft Malware Classification Challenge dataset. Fine-tuning the model using randomly selected 5% labeled samples from the training set still achieved high accuracy of 94.22%. IMCSCL exhibits superior generalization ability, faster convergence speed, and better training stability. Moreover, contrastive learning significantly reduces malware labeling costs while effectively enhancing detection performance. © 2023 IEEE.

关键词： Image classification

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Adversarial Example Detection for Deep Neural Networks: A Review 8

Adversarial Example Detection for Deep Neural Networks: A Re...

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8th International Conference on Data science in Cyberspace, DSC 2023

作者： Zhao, Chongyang Li, Hu Wang, Dongxia Liu, Ruiqi National Key Laboratory of Science and Technology on Information System Security Beijing China

ISBN: (纸本)9798350331035

Deep neural networks have been widely applied in various critical domains. However, they are vulnerable to the threat of adversarial examples. It is challenging to make deep neural networks inherently robust to adversarial examples, while adversarial example detection offers advantages such as not affecting model classification accuracy. This paper introduces common adversarial attack methods and provides an explanation of adversarial example detection. Recent advances in adversarial example detection methods are categorized into two major classes: statistical methods and adversarial detection networks. The evolutionary relationship among different detection methods is discussed. Finally, the current research status in this field is summarized, and potential future directions are highlighted. © 2023 IEEE.

关键词： adversarial detection adversarial example deep neural network

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Combining Local Electromagnetic Scattering and Global Structure Features for SAR Open Set Recognition

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 12572-12587页

作者： Lin, Qinjie Sun, Hao Xu, Yanjie Wang, Junyu Ji, Kefeng Kuang, Gangyao National University of Defense Technology State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and Technology Changsha410073 China

Automatic target recognition (ATR) is crucial for synthetic aperture radar (SAR) image interpretation. However, existing SAR ATR primarily rely on algorithms from the field of computer vision, many methods have not adequately considered the imaging sensitivity of SAR images. Moreover, SAR ATR typically follows the closed set assumption, but in dynamic and open real-world environments, SAR systems may encounter target classes that have not been seen during training. To address these issues, this paper proposes a SAR open set recognition (OSR) method that combines local electromagnetic scattering and global structure features. The global structural features focus on the overall relationship between target and background, while the local electromagnetic scattering features can effectively capture the scattering characteristics of target. Hence, we construct a global and local feature guidance (GLGE) network, fuses these complementary features as prior knowledge to guide deep features. Then, a class-anchor-based loss function is constructed by Anchor loss and Tuple loss, which cluster the features of known classes targets around predefined class anchors. Finally, the distance ratio is calculated to identify known classes targets and reject unknown classes targets. The experimental results on the MSTAR and SAR-ACD datasets show that our method outperforms other OSR methods in recall, precision, F1, and accuracy, demonstrating a superior performance in OSR. © 2008-2012 IEEE.

关键词： Automatic target recognition

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m2Vib: 2D Vibration Measurement Using a Single mmWave Radar 30

m2Vib: 2D Vibration Measurement Using a Single mmWave Radar

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30th IEEE International Conference on Parallel and Distributed systems, ICPADS 2024

作者： Wang, Haolin Xu, Wei Li, Zezhao Yang, Yanni Huang, Zhijian Shandong University School of Computer Science and Technology Qingdao China National Key Laboratory of Science and Technology on Information System Security China

ISBN: (纸本)9798331515966

Two-dimensional vibration measurement is essential for monitoring structure and machine health, especially providing more information than those 1D solutions. However, most existing 2D vibration monitoring methods require multi-dimension sensors, which can be costly for large-scale deployment. In this paper, we propose m^2 Vib, the first work that can realize accurate 2D vibration measurement using a single mmWave radar. Our system is achieved by creating a virtual radar with non-line-of-sight (NLoS) signals from a nearby reflector (e.g., wall) to offer the 2nd-dimension vibration observations. We further establish a geometric model to unveil the relationship between 2D vibration displacement and mmWave signal. Such an idea still encounters challenges from significantly attenuated NLoS signals and low-resolution geometric parameters from the commercial mmWave radar. Thus, we design a new retroreflector to enhance NLoS signals and advanced signal processing methods to obtain fine-grained geometric parameters. Extensive experimental results show that we can achieve sub-mm level 2D vibration measurement with an average vibration displacement error of 62.2 um and frequency error of 0.01 Hz in the X-axis and Y-axis. © 2024 IEEE.

关键词： Vibration measurement

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Impacts of Land–Atmosphere Coupling on Summer Extreme Hot-Humid Compound Events over Southern Eurasia under Different Sea Surface Temperature Backgrounds

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Advances in Atmospheric sciences 2025年第4期42卷 744-760页

作者： Yajing QI Haishan CHEN Siguang ZHU State Key Laboratory of Climate System Prediction and Risk Management/Key Laboratory of Meteorological Disaster Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjing 210044China School of Atmospheric Sciences Nanjing University of Information Science and TechnologyNanjing 210044China

Land–atmosphere coupling and sea surface temperature(SST)anomalies both have essential impacts on weather and climate *** on the ERA5 reanalysis dataset and the CESM1.2.2 model,this study investigates the influence of land–atmosphere coupling on summer extreme hot-humid events(EHHE)over southern Eurasia under different SST *** results suggest that coupling causes near-surface air temperature increases that exceed 0.5℃.From 1961 to 2020,the frequency of EHHE has continuously increased,and is closely related to soil moisture anomalies in the northern Indian Peninsula(IDP)and the middle and lower reaches of the Yangtze River(YRB).Numerical simulations further demonstrate that land–atmosphere coupling raises the risk of EHHE by 25.4%.In a typical El Niño SST background state,intensified land–atmosphere coupling tends to produce notable increases in the frequency of *** dominant processes that land–atmosphere coupling affects the EHHE variations are evidently different between these two *** surface thermal anomalies predominate in the IDP,while moisture conditions are more critical in the *** warm SST anomalies exist,dry soil anomalies in the IDP are prominent,and evaporation is constrained,increasing sensible heat *** geopotential height anomalies are significant,combined with adiabatic warming induced by descending motion and a noticeable warm center in the near-surface *** southward shift of the westerly jet enhances divergence over *** anticyclonic circulation anomalies over the western Pacific are conducive to guiding moisture transport to the YRB,providing a favorable circulation background for the development of summer EHHE.

关键词： land-atmosphere coupling sea surface temperature extreme hot-humid events southern Eurasia

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Enhanced influence of the North Atlantic Oscillation on winter snowfall in northern China since 2000

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science China Earth sciences 2025年第4期68卷 1236-1244页

作者： Botao ZHOU Chuer GUO Yuepeng HU Wenxin XIE Bo SUN Tingting HAN Ning SHI State Key Laboratory of Climate System Prediction and Risk Management/Key Laboratory of Meteorological Disaster Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjing210044China School of Atmospheric Sciences Nanjing University of Information Science and TechnologyNanjing210044China Zhejiang Meteorological Observatory Hangzhou310002China

Because of the profound impacts of snowfall in northern China on the economy society and human lives,it is essential to understand the physical mechanisms behind the variability of snowfall in this *** on the observational and reanalysis data during 1961–2018,this study examines the relationship of winter snowfall over northern China with the North Atlantic Oscillation(NAO).The results show that their relationship experiences an interdecadal change around *** 2000–2018,the NAO is significantly and negatively correlated to winter snowfall in northern *** the NAO is in the negative phase,the East Asian subtropical jet and polar front jet tend to move northward and southward,respectively,concomitant with an anomalous cyclonic circulation from Lake Balkhash to Lake Baikal in the middle and lower *** an atmospheric background favors the increase of snowfall over northern China by empowering the interactions of cold air with moist airflows in the target ***,during 1981–1999,the association of the NAO with the above atmospheric circulations seems inconspicuous,thereby reducing its relation to winter snowfall in northern *** investigation suggests that the enhancement of the connection between the NAO and aforementioned atmospheric circulations may result from the westward displacement of the NAO southern center from the former period to the latter period.

关键词： Winter snowfall Northern China North Atlantic Oscillation Interdecadal change Atmospheric circulations

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Low-overhead fault-tolerant error correction scheme based on quantum stabilizer codes

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Chinese Physics B 2022年第4期31卷 143-150页

作者： Xiu-Bo Chen Li-Yun Zhao Gang Xu Xing-Bo Pan Si-Yi Chen Zhen-Wen Cheng Yi-Xian Yang Information Security Center State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing 100876China School of Information Science and Technology North China University of TechnologyBeijing 100144China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu 610025China

Fault-tolerant error-correction(FTEC)circuit is the foundation for achieving reliable quantum computation and remote ***,designing a fault-tolerant error correction scheme with a solid error-correction ability and low overhead remains a significant *** this paper,a low-overhead fault-tolerant error correction scheme is proposed for quantum communication ***,syndrome ancillas are prepared into Bell states to detect errors caused by channel *** propose a detection approach that reduces the propagation path of quantum gate fault and reduces the circuit depth by splitting the stabilizer generator into X-type and ***,a syndrome extraction circuit is equipped with two flag qubits to detect quantum gate faults,which may also introduce errors into the code block during the error detection ***,analytical results are provided to demonstrate the fault-tolerant performance of the proposed FTEC scheme with the lower overhead of the ancillary qubits and circuit depth.

关键词： fault-tolerant error correction quantum stabilizer code gate fault quantum circuit

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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

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Super-resolution reconstruction of single image for latent features

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Computational Visual Media 2024年第6期10卷 1219-1239页

作者： Xin Wang Jing-Ke Yan Jing-Ye Cai Jian-Hua Deng Qin Qin Yao Cheng School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu 610000 China State Key Laboratory of Rail Transit Vehicle System Southwest Jiaotong UniversityChengdu 610000China School of Marine Engineering Guilin University of Electronic TechnologyGuilin 541000China School of Computer and Information Security Guilin University of Electronic TechnologyGuilin 541000China

Single-image super-resolution(SISR)typically focuses on restoring various degraded low-resolution(LR)images to a single high-resolution(HR)***,during SISR tasks,it is often challenging for models to simultaneously maintain high quality and rapid sampling while preserving diversity in details and texture *** challenge can lead to issues such as model collapse,lack of rich details and texture features in the reconstructed HR images,and excessive time consumption for model *** address these problems,this paper proposes a Latent Feature-oriented Diffusion Probability Model(LDDPM).First,we designed a conditional encoder capable of effectively encoding LR images,reducing the solution space for model image reconstruction and thereby improving the quality of the reconstructed *** then employed a normalized flow and multimodal adversarial training,learning from complex multimodal distributions,to model the denoising *** so boosts the generative modeling capabilities within a minimal number of sampling *** comparisons of our proposed model with existing SISR methods on mainstream datasets demonstrate that our model reconstructs more realistic HR images and achieves better performance on multiple evaluation metrics,providing a fresh perspective for tackling SISR tasks.

关键词： image superresolution reconstruction denoising diffusion probabilistic model normalized flow adversarial neural network variational auto-encoder

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