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An efficient quantum meet-in-the-middle attack against NTRU-2005

Chinese Science Bulletin 2013年第28期58卷 3514-3518页

作者： WANG Hong MA Zhi MA ChuanGui State Key Laboratory of Mathematical Engineering and Advanced Computing

NTRU is one of the most widely used public-key cryptosystems and its security has been an active research *** paper proposes a new way to find NTRU-2005 private *** algorithm is based on meet-in-the-middle attack and a quantum algorithm for searching the fixed weight *** with the current classical and quantum meet-in-the-middle attacks,our algorithm has lower time and space ***,this attack can also be applied against different versions of *** result can help to understand the security of NTRU better.

关键词：中间人攻击量子算法 NTRU 空间复杂度公钥密码安全性私钥搜索

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Research Progress of Reverse Monte Carlo and Its Application in Josephson Junction Barrier Layer

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Computer Modeling in engineering & Sciences 2023年第12期137卷 2077-2109页

作者： Junling Qiu Huihui Sun Shuya Wang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001China

As indispensable components of superconducting circuit-based quantum computers,Josephson junctions determine how well superconducting qubits *** Monte Carlo(RMC)can be used to recreate Josephson junction’s atomic structure based on experimental data,and the impact of the structure on junctions’properties can be investigated by combining different analysis *** order to build a physical model of the atomic structure and then analyze the factors that affect its performance,this paper briefly reviews the development and evolution of the RMC *** also summarizes the modeling process and structural feature analysis of the Josephson junction in combination with different feature extraction techniques for electrical characterization ***,the obstacles and potential directions of Josephson junction modeling,which serves as the theoretical foundation for the production of superconducting quantum devices at the atomic level,are discussed.

关键词： Reverse Monte Carlo Josephson junction alumina barrier layer

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Replace2Self: Self-Supervised Denoising based on Voxel Replacing and Image Mixing for Diffusion MRI

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IEEE Transactions on Medical Imaging 2025年 PP卷 PP页

作者： Wu, Linhai Wang, Lihui Deng, Zeyu Zhu, Yuemin Wei, Hongjiang Guizhou University Key Laboratory of Advanced Medical Imaging and Intelligent Computing of Guizhou Province Engineering Research Center of Text Computing & Cognitive Intelligence Ministry of Education State Key Laboratory of Public Big Data College of Computer Science and Technology 550025 China Univ Lyon INSA Lyon CNRS Inserm CREATIS UMR 5220 LyonF-69621 France Shanghai Jiao Tong University School of Biomedical Engineering Shanghai200030 China

Low signal to noise ratio (SNR) remains one of the limitations of diffusion weighted (DW) imaging. How to suppress the influence of noise on the subsequent analysis about the tissue microstructure is still challenging. This work proposed a novel self-supervised learning model, Replace2Self, to effectively reduce spatial correlated noise in DW images. Specifically, a voxel replacement strategy based on similar block matching in Q-space was proposed to destroy the correlations of noise in DW image along one diffusion gradient direction. To alleviate the signal gap caused by the voxel replacement, an image mixing strategy based on complementary mask was designed to generate two different noisy DW images. After that, these two noisy DW images were taken as input, and the non-correlated noisy DWimage after voxel replacement was taken as learning target, a denoising network was trained for denoising. To promote the denoising performance, a complementary mask mixing consistency loss and an inverse replacement regularization loss were also proposed. Through the comparisons against several existing DW image denoising methods on extensive simulation data with different noise distributions, noise levels and b-values, as well as the acquisition datasets and the ablation experiments, we verified the effectiveness of the proposed method. Regardless of the noise distribution and noise level, the proposed method achieved the highest PSNR, which was at least 1.9% higher than the suboptimal method when the noise level reaches 10%. Furthermore, our method has superior generalization ability due to the use of the proposed strategies. © 2025 IEEE. All rights reserved.

关键词： Signal to noise ratio

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Dynamic evolution of collective emotions in social networks: a case study of Sina weibo

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Science China(Information Sciences) 2013年第7期56卷 150-167页

作者： XIONG XiaoBing ZHOU Gang HUANG YongZhong CHEN HaiYong XU Ke State Key Laboratory of Mathematical Engineering and Advanced Computing State Key Laboratory of Software Development Environment Beihang University

Emotion is a fundamental object of human existence and determined by a complex set of factors. With the rapid development of online social networks (OSNs), more and more people would like to express their emotion in OSNs, which provides wonderful opportunities to gain insight into how and why individual emotion is evolved in social network. In this paper, we focus on emotion dynamics in OSNs, and try to recognize the evolving process of collective emotions. As a basis of this research, we first construct a corpus and build an emotion classifier based on Bayes theory, and some effective strategies (entropy and salience) are introduced to improve the performance of our classifier, with which we can classify any Chinese tweet into a particular emotion with an accuracy as high as 82%. By analyzing the collective emotions in our sample networks in detail, we get some interesting findings, including a phenomenon of emotion synchronization between friends in OSNs, which offers good evidence for that human emotion can be spread from one person to another. Furthermore, we find that the number of friends has strong correlation with individual emotion. Based on those useful findings, we present a dynamic evolution model of collective emotions, in which both self-evolving process and mutual-evolving process are considered. To this end, extensive simulations on both real and artificial networks have been done to estimate the parameters of our emotion dynamic model, and we find that mutual-evolution plays a more important role than self-evolution in the distribution of collective emotions. As an application of our emotion dynamic model, we design an efficient strategy to control the collective emotions of the whole network by selecting seed users according to k-core rather than degree.

关键词： online social network emotion classifier emotion spread emotion dynamic model emotion controlling

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Revocable Broadcast Encryption with Constant Ciphertext and Private key Size

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Chinese Journal of Electronics 2019年第4期28卷 690-697页

作者： JIA Hongyong CHEN Yue YANG Kuiwu GUO Yuanbo WANG Zhiwei Zhengzhou University State Key Laboratory of Mathematical Engineering and Advanced Computing Nanjing University of Post and Communications

In a revocable broadcast encryption scheme, the group manager can flexibly set revoked users who cannot decrypt the ciphertext. Many applications of the revocable broadcast encryption have been found in the secure cloud data sharing. An adaptively secure revocable broadcast encryption system with constant ciphertext and private key size under standard assumptions is more suitable for use in the cloud environment. Few existing revocable broadcast encryption schemes meet such a requirement. We propose a revocable broadcast encryption scheme with constant size ciphertext and private key by combining the RSA cryptographic accumulator with an efficient identity based encryption system. We prove it to be adaptively secure under standard assumptions using dual system encryption techniques.

关键词： Cryptographic accumulator Broadcast encryption Revocable Dual system encryption Cloud data sharing

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An advanced Automatic Construction Method of ROP

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Wuhan University Journal of Natural Sciences 2015年第2期20卷 119-128页

作者： OUYANG Yongji WANG Qingxian PENG Jianshan ZENG Jie State Key Laboratory of Mathematical Engineering and Advanced Computing

Automatic return oriented programming （ROP） technology can effectively improve the efficiency of ROP constructed, but the existing research results still have some shortcomings including needing more address space, poor generality. In order to solve these problems, this paper presents an improved ROP auto-constructor QExtd. Firstly, we design a Turing-complete language QExtdL and provide the basis of gadgets analysis. Secondly, we represent the MI instruction and realize precise process of side-effect instructions for improving the efficiency of automatic construction. At last, we establish a three-layer language conversion mechanism, making it convenient for users to construct ROP. Theoretical and experimental data show that the QExtd automatic construction method is much better than the ROPgadget based on syntax. In addition, the proposed method succeeds in constructing gadgets of ROP with the probability of 84% for programs whose sizes are more than 20 KB and whose directory is ＂/usr/bin＂ in Ubuntu, which proves that the construction capability improves significantly.

关键词： return oriented programing (ROP) gadget automatic construction Turing-complete

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Blockchain-Enabled Secure, Fair and Scalable Data Sharing in Zero-Trust Edge-End Environment

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IEEE Journal on Selected Areas in Communications 2025年

作者： Xu, Xiaolong Meng, Ke Xiang, Haolong Cui, Guangming Xia, Xiaoyu Dou, Wanchun Nanjing210044 China Nanjing University of Information Science and Technology School of Software and the Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services Nanjing210044 China RMIT University School of Computing Technologies MelbourneVIC3000 Australia Nanjing University State Key Laboratory for Novel Software Technology Nanjing210023 China

In edge computing, the Zero-Trust Security Model (ZTSM), as a key enabling technology for next-generation networks, plays a crucial role in providing authentication for addressing data sharing concerns, such as frequent data breaches, data misuse, and cyberattacks. However, due to the complexity and diversity of edge environments, ZTSM struggles to meet the security requirements of data sharing frameworks solely through enhanced authentication. Consequently, such frameworks with ZTSM still face challenges in ensuring data integrity, evaluating various node behaviors, and coping with the increasing complexity of node attributes. To address these issues, we propose a blockchain-enabled secure, fair and scalable data sharing framework in a zero-trust edge-end environment in this paper. Specifically, we first propose a Merkle forest-based data storage model for the classified storage of loosely coupled data, consequently enhancing the scalability of the model. Then, we design a node behavior-based reputation assessment mechanism to ensure fairness during data sharing. Moreover, a data sharing protocol supervised by smart contract is proposed, working with the aforementioned storage and assessment schemes, to ensure the security of data sharing. Finally, comprehensive security analysis validates the security, fairness and scalability of the proposed framework. Extensive experimental results show that, as transaction volume grows, the time cost of data traversal in the storage model becomes progressively more efficient. Additionally, when the size of the smart contract is increased tenfold, the maximum time cost of the data sharing protocol rises by only 4.98 times. © 1983-2012 IEEE.

关键词： Data integrity

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Combo Packet:An Encryption Traffic Classification Method Based on Contextual Information

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Computers, Materials & Continua 2024年第4期79卷 1223-1243页

作者： Yuancong Chai Yuefei Zhu Wei Lin Ding Li State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering UniversityZhengzhou450001China

With the increasing proportion of encrypted traffic in cyberspace, the classification of encrypted traffic has becomea core key technology in network supervision. In recent years, many different solutions have emerged in this *** methods identify and classify traffic by extracting spatiotemporal characteristics of data flows or byte-levelfeatures of packets. However, due to changes in data transmission mediums, such as fiber optics and satellites,temporal features can exhibit significant variations due to changes in communication links and transmissionquality. Additionally, partial spatial features can change due to reasons like data reordering and *** with these challenges, identifying encrypted traffic solely based on packet byte-level features is significantlydifficult. To address this, we propose a universal packet-level encrypted traffic identification method, ComboPacket. This method utilizes convolutional neural networks to extract deep features of the current packet andits contextual information and employs spatial and channel attention mechanisms to select and locate effectivefeatures. Experimental data shows that Combo Packet can effectively distinguish between encrypted traffic servicecategories (e.g., File Transfer Protocol, FTP, and Peer-to-Peer, P2P) and encrypted traffic application categories (e.g.,BitTorrent and Skype). Validated on the ISCX VPN-non VPN dataset, it achieves classification accuracies of 97.0%and 97.1% for service and application categories, respectively. It also provides shorter training times and higherrecognition speeds. The performance and recognition capabilities of Combo Packet are significantly superior tothe existing classification methods mentioned.

关键词： Encrypted traffic classification packet-level convolutional neural network attention mechanisms

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An efficient and practical threshold gateway-oriented password-authenticated key exchange protocol in the standard model

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Science China(Information Sciences) 2017年第7期60卷 130-143页

作者： Fushan WEI Jianfeng MA Ruijie ZHANG Chuangui MA Xuan WANG State Key Laboratory of Integrated Service Networks Xidian University State Key Laboratory of Mathematical Engineering and Advanced Computing The PLA Information Engineering University Engineering University of CAPF

With the assistance of an authentication server, a gateway-oriented password-authenticated key exchange(GPAKE) protocol can establish a common session key shared between a client and a gateway. Unfortunately, a GPAKE protocol becomes totally insecure if an adversary can compromise the authentication server and steal the passwords of the clients. In order to provide resilience against adversaries who can hack into the authentication server, we propose a threshold GPAKE protocol and then present its security proof in the standard model based on the hardness of the decisional Diffie-Hellman(DDH) problem. In our proposal,the password is shared among n authentication servers and is secure unless the adversary corrupts more than t + 1 servers. Our protocol requires n > 3t servers to work. Compared with existing threshold PAKE protocols,our protocol maintains both stronger security and greater efficiency.

关键词： password key exchange gateway threshold provable security

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Method based on GSCPN for network vulnerability analysis

Journal of Software

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Journal of Software 2013年第8期8卷 2032-2038页

作者： Gao, Xiang Zhu, Yue-Fei Fei, Jin-Long Han, Tao State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450002 China

With the development of network security research, network attack modeling and analysis techniques have been paid more and more attention. A generalized stochastic colored Petri Net (GSCPN) Model is proposed. To each attack, a GSCPN model is constructed to describe the relation of components graphically. Algorithm to construct a composite attack and method for network vulnerability analysis are delivered also. The exploitation cost of vulnerabilities is estimated. The method is relatively simple, which is different from traditional method. The network example further validates the proposed method for network vulnerability analysis. © 2013 ACADEMY PUBLISHER.

关键词： Network security

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