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Improved lower bound for the complexity of unique shortest vector problem

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Cybersecurity 2024年第3期7卷 102-110页

作者： Baolong Jin Rui Xue State Key Laboratory of information security Institute of Information EngineeringChinese Academy of SciencesBeijing 100085China School of Cyber security University of Chinese Academy of SciencesBeijing 100049China

Unique shortest vector problem(uSVP)plays an important role in lattice based *** cryptographic schemes based their security on *** the cofidence of those applications,it is essential to clarify the complex-ity of uSVP with different ***,proving the NP-hardness of usVP appears quite *** the state of the art,we are even not able to prove the NP-hardness of usVP with constant *** this work,we gave a lower bound for the hardness of usVP with constant parameters,*** proved that uSVP is at least as hard as gap shortest vector problem(GapSVP)with gap of O(√n/log(n)),which is in NP n *** previous works,our reduction works for paramters in a bigger range,especially when the constant hidden by the big-O in GapsVP is smallerthan1.

关键词： Computational complexity Unique shortest vector problem Bounded distance decoding Complexity reduction

Lightweight Res-Connection Multi-Branch Network for Highly Accurate Crowd Counting and Localization

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Computers, Materials & Continua 2024年第5期79卷 2105-2122页

作者： Mingze Li Diwen Zheng Shuhua Lu College of information and Cyber security People’s Public Security University of ChinaBeijing102600China

Crowd counting is a promising hotspot of computer vision involving crowd intelligence analysis,achieving tremendous success recently with the development of deep ***,there have been stillmany challenges including crowd multi-scale variations and high network complexity,*** tackle these issues,a lightweight Resconnection multi-branch network(LRMBNet)for highly accurate crowd counting and localization is ***,using improved ShuffleNet V2 as the backbone,a lightweight shallow extractor has been designed by employing the channel compression mechanism to reduce enormously the number of network parameters.A light multi-branch structure with different expansion rate convolutions is demonstrated to extract multi-scale features and enlarged receptive fields,where the information transmission and fusion of diverse scale features is enhanced via residual *** addition,a compound loss function is introduced for training themethod to improve global context information *** proposed method is evaluated on the SHHA,SHHB,UCF-QNRF and UCF_CC_50 public *** accuracy is better than those of many advanced approaches,while the number of parameters is *** experimental results show that the proposed method achieves a good tradeoff between the complexity and accuracy of crowd counting,indicating a lightweight and high-precision method for crowd counting.

关键词： Crowd counting Res-connection multi-branch compound loss function

Heterophilic Graph Neural Network Based on Spatial and Frequency Domain Adaptive Embedding Mechanism

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1701-1731页

作者： Lanze Zhang Yijun Gu Jingjie Peng College of information and Cyber security People’s Public Security University of ChinaBeijing100038China

Graph Neural Networks(GNNs)play a significant role in tasks related to homophilic *** GNNs,based on the assumption of homophily,employ low-pass filters for neighboring nodes to achieve information aggregation and ***,in heterophilic graphs,nodes from different categories often establish connections,while nodes of the same category are located further apart in the graph *** characteristic poses challenges to traditional GNNs,leading to issues of“distant node modeling deficiency”and“failure of the homophily assumption”.In response,this paper introduces the Spatial-Frequency domain Adaptive Heterophilic Graph Neural Networks(SFA-HGNN),which integrates adaptive embedding mechanisms for both spatial and frequency domains to address the aforementioned ***,for the first problem,we propose the“Distant Spatial Embedding Module”,aiming to select and aggregate distant nodes through high-order randomwalk transition probabilities to enhance modeling *** the second issue,we design the“Proximal Frequency Domain Embedding Module”,constructing adaptive filters to separate high and low-frequency signals of nodes,and introduce frequency-domain guided attention mechanisms to fuse the relevant information,thereby reducing the noise introduced by the failure of the homophily *** deploy the SFA-HGNN on six publicly available heterophilic networks,achieving state-of-the-art results in four of ***,we elaborate on the hyperparameter selection mechanism and validate the performance of each module through experimentation,demonstrating a positive correlation between“node structural similarity”,“node attribute vector similarity”,and“node homophily”in heterophilic networks.

关键词： Heterophilic graph graph neural network graph representation learning failure of the homophily assumption

SAT-Based Automatic Searching for Differential and Linear Trails: Applying to CRAX

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Chinese Journal of Electronics 2024年第1期33卷 72-79页

作者： Yiyi HAN Caibing WANG Zhongfeng NIU Lei HU State Key Laboratory of information security Institute of Information Engineering Chinese Academy of Sciences School of Cyber security University of Chinese Academy of Sciences

Boolean satisfiability problem(SAT) is now widely applied in differential cryptanalysis and linear cryptanalysis for various cipher *** generated many excellent results for some ciphers,for example,*** this research,we study the differential and linear propagations through the operations of addition,rotation and XOR(ARX),and construct the SAT *** apply the models to CRAX to search differential trails and linear trails *** this sense,our contnbution can be broadly divided into two *** give the bounds for differential and linear cryptanalysis of Alzette both up to 12 steps,by which we present a 3-round differential attack and a 3-round linear attack for *** construct a 4-round key-recovery attack for CRAX with time complexity289times of 4-round encryption and data complexity 225.

关键词： Ciphers Encryption Complexity theory Time complexity

Attention-Enhanced Voice Portrait Model Using Generative Adversarial Network

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Computers, Materials & Continua 2024年第4期79卷 837-855页

作者： Jingyi Mao Yuchen Zhou YifanWang Junyu Li Ziqing Liu Fanliang Bu School of information Network security People’s Public Security University of ChinaBeijing100038China

Voice portrait technology has explored and established the relationship between speakers’ voices and their facialfeatures, aiming to generate corresponding facial characteristics by providing the voice of an unknown *** to its powerful advantages in image generation, Generative Adversarial Networks (GANs) have now beenwidely applied across various fields. The existing Voice2Face methods for voice portraits are primarily based onGANs trained on voice-face paired datasets. However, voice portrait models solely constructed on GANs facelimitations in image generation quality and struggle to maintain facial similarity. Additionally, the training processis relatively unstable, thereby affecting the overall generative performance of the model. To overcome the abovechallenges,wepropose a novel deepGenerativeAdversarialNetworkmodel for audio-visual synthesis, namedAVPGAN(Attention-enhanced Voice Portrait Model using Generative Adversarial Network). This model is based ona convolutional attention mechanism and is capable of generating corresponding facial images from the voice ofan unknown speaker. Firstly, to address the issue of training instability, we integrate convolutional neural networkswith deep GANs. In the network architecture, we apply spectral normalization to constrain the variation of thediscriminator, preventing issues such as mode collapse. Secondly, to enhance the model’s ability to extract relevantfeatures between the two modalities, we propose a voice portrait model based on convolutional attention. Thismodel learns the mapping relationship between voice and facial features in a common space from both channeland spatial dimensions independently. Thirdly, to enhance the quality of generated faces, we have incorporated adegradation removal module and utilized pretrained facial GANs as facial priors to repair and enhance the clarityof the generated facial images. Experimental results demonstrate that our AVP-GAN achieved a cosine similarity of0.511, ou

关键词： Cross-modal generation GANs voice portrait technology face synthesis

TransTM:A device-free method based on time-streaming multiscale transformer for human activity recognition

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Defence Technology（防务技术） 2024年第2期32卷 619-628页

作者： Yi Liu Weiqing Huang Shang Jiang Bobai Zhao Shuai Wang Siye Wang Yanfang Zhang institute of information Engineering Chinese Academy of Sciences School of Cyber SecurityUniversity of Chinese Academy of SciencesBeijingChina School of information Management Beijing Information Science and Technology UniversityBeijingChina

RFID-based human activity recognition(HAR)attracts attention due to its convenience,noninvasiveness,and privacy *** RFID-based HAR methods use modeling,CNN,or LSTM to extract features ***,they have shortcomings:1)requiring complex hand-crafted data cleaning processes and 2)only addressing single-person activity recognition based on specific RF *** solve these problems,this paper proposes a novel device-free method based on Time-streaming Multiscale Transformer called *** model leverages the Transformer's powerful data fitting capabilities to take raw RFID RSSI data as input without ***,we propose a multiscale convolutional hybrid Transformer to capture behavioral features that recognizes singlehuman activities and human-to-human *** with existing CNN-and LSTM-based methods,the Transformer-based method has more data fitting power,generalization,and ***,using RF signals,our method achieves an excellent classification effect on human behaviorbased classification *** results on the actual RFID datasets show that this model achieves a high average recognition accuracy(99.1%).The dataset we collected for detecting RFID-based indoor human activities will be published.

关键词： Human activity recognition RFID Transformer

Robust adaptive radar beamforming based on iterative training sample selection using kurtosis of generalized inner product statistics

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Journal of Systems Engineering and Electronics 2024年第1期35卷 24-30页

作者： TIAN Jing ZHANG Wei School of information and Electronics Beijing Institute of TechnologyBeijing 100081China National Key Laboratory of Electromagnetic Space security Chengdu 610036China

In engineering application,there is only one adaptive weights estimated by most of traditional early warning radars for adaptive interference suppression in a pulse reputation interval(PRI).Therefore,if the training samples used to calculate the weight vector does not contain the jamming,then the jamming cannot be removed by adaptive spatial *** the weight vector is constantly updated in the range dimension,the training data may contain target echo signals,resulting in signal cancellation *** cope with the situation that the training samples are contaminated by target signal,an iterative training sample selection method based on non-homogeneous detector(NHD)is proposed in this paper for updating the weight vector in entire range *** principle is presented,and the validity is proven by simulation results.

关键词： adaptive radar beamforming training sample selection non-homogeneous detector electronic jamming jamming suppression

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

security estimation of LWE via BKW algorithms

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Cybersecurity 2024年第1期7卷 71-87页

作者： Yu Wei Lei Bi Xianhui Lu Kunpeng Wang SKLOIS Institute of Information EngineeringCASBeijingChina School of Cyber security University of Chinese Academy of SciencesBeijingChina

The Learning With Errors(LWE)problem is widely used in lattice-based cryptography,which is the most promising post-quantum cryptography *** are a variety of LWE-solving methods,which can be classified into four groups:lattice methods,algebraic methods,combinatorial methods,and exhaustive *** Blum–Kalai–Wasserman(BKW)algorithm is an important variety of combinatorial algorithms,which was first presented for solving the Learning Parity With Noise(LPN)problem and then extended to solve *** this paper,we give an overview of BKW algorithms for solving *** introduce the framework and key techniques of BKW algorithms and make comparisons between different BKW algorithms and also with lattice methods by estimating concrete security of specific LWE *** also briefly discuss the current problems and potential future directions of BKW algorithms.

关键词： Post-quantum cryptography Learning with errors problem Lattice-based cryptography security estimation