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4th International Conference on Big Data and Security, ICBDS 2022

作者： Zhou, Pei Luo, Xiangyang Du, Shaoyong Shi, Wenqi Guo, Jiashan School of Cyber Science and Engineering Zhengzhou University Zhengzhou450000 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450000 China

ISBN: (纸本)9789819932993

To solve the multi-platform user association problem of complex trajectory matching process and high time cost in cross-platform association positioning of instant messaging users, and at the same time make full use of the information in user trajectories, this paper proposes a supervised learning-based cross-platform instant messaging user association positioning method. The algorithm firstly places probes in the area where the target may appear to obtain user information;then gets user trajectories through the obtained user distance information and time information;selects user features through the classification algorithm of supervised learning, and designs a cross-platform instant messaging user association localization method based on supervised learning, so as to increase the association efficiency and accuracy of cross-platform instant messaging user association. The method conducts specific experiments for the most commonly used instant messaging tools in China, WeChat and Stranger users, and the results show that the method can achieve efficient and reliable association for these two types of instant messaging users. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Trajectories

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A Review of Field Text Analysis

A Review of Field Text Analysis

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2021 IEEE Conference on Telecommunications, Optics and Computer Science, TOCS 2021

作者： Li, Zhuolun Kang, Fei Yu, Pu Shu, Hui Zhengzhou University School of Software Zhengzhou China Meac State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665424981

Field text analysis is the process of using natural language processing technology to understand the Text and extract information from unstructured text data. In recent years, due to the increasing maturity of machine learning technology, higher requirements have been put forward for field text analysis. This review first introduces the process of Text preprocessing and the development of text representation. Secondly, it summarizes the four typical techniques of text analysis, including named entity recognition, relation extraction, extractive text summarization, and text classification. Finally, for each typical technology, it introduces the commonly used methods and part of the researcher's exploration of this technology. © 2021 IEEE.

关键词： Text processing

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A Graph Reasoning Model Based on Multiple Types of Nodes 7

A Graph Reasoning Model Based on Multiple Types of Nodes

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7th International Conference on Big Data and Information Analytics, BigDIA 2021

作者： Liu, Yibing Huo, Lijun Zhou, Gang Information Engineering University State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China National University of Defense Technology Key Laboratory of Information System Engineering Changsha China

ISBN: (纸本)9781665424660

Multi-hop machine reading comprehension (MRC) depends on the model to answer a semantically related question based on the given supporting text. In this study, inspired by previous research about Graph Neural Network(GNN), we develop a new graph covering three kinds of nodes: Sentence, Entity, Candidate. A corresponding MRC method based on graph inference is proposed, called SEC reasoner. The advantage of SECr is that it adopts different granular information as graph nodes, which can execute a more comprehensive reasoning. Our proposed model first initialize the node representations by co-Attention, multi-head attention and self-Attention based on context embedding. SECr then employs GNN based information transfer algorithms to collect evidences from the node encoding, and calculates a score for choosing the answer. In experiments, we evaluate the model on two popular benchmark datasets-WikiHop and MedHop. SECr reachs accuracy rates of 71.6%, 63.1% respectively, which is a competitive result. In addition, a comprehensive analysis proves the effectiveness and interpretability of the SECr. © 2021 IEEE.

关键词： Semantics

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A Review on IoT Botnet 2021

A Review on IoT Botnet

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2nd International Conference on computing and Data Science, CONF-CDS 2021

作者： Zhao, Hao Shu, Hui Xing, Ying State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Software College Zhongyuan University of Technology Zhengzhou China

ISBN: (纸本)9781450389570

The rapid development of the Internet of Things (IoT) also generates security threats that cannot be ignored. This paper lists the development history of botnets, introduces representative IoT botnets, and reveals their new characteristics. The botnet mechanism and characteristics of IoT botnets are analyzed in depth from three aspects: composition structure, life cycle, and attack behavior, and are compared with traditional botnets. Networks for comparison. The analysis discusses the details of IoT botnet technologies such as scanning discovery, covert communication and survival residency. Summarizes the research status of IoT botnet detection technologies and gives future directions. Finally, the importance of preventing IoT botnets and solving IoT security problems is discussed. © 2021 ACM.

关键词： Internet of things

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Preparation and Simulation of Quantum states of Matrices 6

Preparation and Simulation of Quantum States of Matrices

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6th International Conference on Electronic Information Technology and Computer engineering, EITCE 2022

作者： Liu, Zhengyu Liu, Xiaonan Xie, Haoshan Zhao, Chenyan School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou450000 China National Supercomputing Center in Zhengzhou Zhengzhou450000 China State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Zhengzhou450000 China

ISBN: (纸本)9781450397148

A basic problem of quantum computing is how to effectively express classical data in quantum systems. This problem is called state preparation problem, and the process of preparing quantum states is called coding. In this paper, the classical data of matrix is transformed into quantum states in the form of amplitude coding and simulated. This paper first introduces the detailed process of matrix transformation into the linear combination of quantum ground state, then designs a quantum circuit model to realize amplitude coding according to the idea of binary tree model and quantum random walk algorithm, and finally simulates the three matrices on IBM quantum cloud platform, and analyzes and introduces many situations. The experimental results verify the feasibility of converting the matrix into quantum states by amplitude coding, analyze the causes of errors in the experimental process, and put forward the corresponding solutions. This paper introduces in detail the whole process of matrix conversion to quantum states and the construction of quantum circuits for simulation. Compared with the existing experiments, the quantum circuits constructed in this paper are shorter in length, less in number of quantum gates, and more versatile. © 2022 Association for computing Machinery.

关键词： Matrix algebra

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Unraveling the Morphological and Energetic Properties of 2PACz Self-Assembled Monolayers Fabricated With Upscaling Deposition Methods

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Energy & Environmental Materials 2025年第2期8卷 291-304页

作者： Silvia Mariotti Ilhem Nadia Rabehi Congyang Zhang Xiaomin Huo Jiahao Zhang Penghui Ji Tianhao Wu Tongtong Li Shuai Yuan Xiaomin Liu Ting Guo Chenfeng Ding Hengyuan Wang Annalisa Bruno Luis K.Ono Yabing Qi Energy Materials and Surface Sciences Unit(EMSSU) Okinawa Institute of cience and Technology Graduate University(OIST)Okinawa 904-0495Japan State Key Laboratory of Organic Electronics and Information Displays&Institute of Advanced Materials(IAM) Nanjing University of Posts&TelecommunicationsNanjing 210023China School of Physical and Mathematical Science&School of Materials Science Engineering&EEnergy Research Institute NTU Nanyang Technological University Singapore 639798Singapore

Self-assembled monolayers(SAMs)are widely used as hole transport materials in inverted perovskite solar cells,offering low parasitic absorption and suitability for semitransparent and tandem solar *** SAMs have shown to be promising in small-area devices(≤1 cm^(2)),their application in larger areas has been limited by a lack of knowledge regarding alternative deposition methods beyond the common spin-coating ***,we compare spin-coating and upscalable methods such as thermal evaporation and spray-coating for[2-(9H-carbazol-9-yl)ethyl]phosphonic acid(2PACz),one of the most common carbazole-based *** impact of these deposition methods on the device performance is investigated,revealing that the spray-coating technique yields higher device ***,our work provides guidelines for the deposition of SAM materials for the fabrication of perovskite solar *** addition,we provide an extensive characterization of 2PACz films focusing on thermal evaporation and spray-coating methods,which allow for thicker 2PACz *** is found that the optimal 2PACz deposition conditions corresponding to the highest device performances do not always correlate with the monolayer characteristics.

关键词： 2PACz Evaporation Perovskite solar cells Self-assembled monolayer Spray-coating

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Shields for Digital Images: A Watermarking Method with KAN Block and Simulation-Enhanced Noise Pool to Resist Screen-Camera Attacks

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IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Guo, Daidou Qin, Chuan Luo, Xiangyang Feng, Guorui Zhang, Xinpeng University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450000 China Henan Key Laboratory of Cyberspace Situation Awareness Zhengzhou450001 China Shanghai University School of Communication and Information Engineering Shanghai200444 China

To address the issues of privacy leakage and copyright infringement in screen-camera scenarios, we propose a robust image watermarking method, which incorporates kolmogorov-arnold network (KAN) blocks and a simulation-enhanced noise pool to resist screen-camera noise attacks. Specifically, we first modify the traditional convolutional blocks for processing high-dimensional features in the U-Net-based encoder to KAN blocks. This operation enhances the ability of encoder to model nonlinear relationships between complex features, while preserving global structure of the original image and minimizing the damage to local details caused by watermark embedding, thereby improving visual quality of the watermarked image. Additionally, to enhance the robustness of the proposed method against complex screen-camera noise attacks, a simulation-enhanced noise pool containing mathematical models and a deep noise simulation network, called NSim-Net, is designed. Especially, in NSim-Net, adversarial training between the simulator based on the improved U-Net and the discriminator based on PatchGAN effectively improves the ability to simulate complex noise. Experimental results demonstrate that, compared to typical screen-camera resilient watermarking methods, the watermarked image generated by the proposed method achieves a maximum peak signal-to-noise ratio (PSNR) improvement of 4.78 dB. Furthermore, based on our simulation-enhanced noise pool, the watermark extraction accuracy of the proposed method exceeds 98% under various screen-camera noise attacks. © 1991-2012 IEEE.

关键词： Image enhancement

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Medical image registration and its application in retinal images:a review

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Visual computing for Industry,Biomedicine,and Art 2024年第1期7卷 142-164页

作者： Qiushi Nie Xiaoqing Zhang Yan Hu Mingdao Gong Jiang Liu Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Center for High Performance Computing and Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Singapore Eye Research Institute Singapore 169856Singapore State Key Laboratory of Ophthalmology Optometry and Visual ScienceEye HospitalWenzhou Medical UniversityWenzhou 325027China

Medical image registration is vital for disease diagnosis and treatment with its ability to merge diverse informa-tion of images,which may be captured under different times,angles,or *** several surveys have reviewed the development of medical image registration,they have not systematically summarized the existing med-ical image registration *** this end,a comprehensive review of these methods is provided from traditional and deep-learning-based perspectives,aiming to help audiences quickly understand the development of medical image *** particular,we review recent advances in retinal image registration,which has not attracted much *** addition,current challenges in retinal image registration are discussed and insights and prospects for future research provided.

关键词： Computer-aided diagnosis Medical image registration Deep learning Generative model Transformer Retina

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Immune Defense: A Novel Adversarial Defense Mechanism for Preventing the Generation of Adversarial Examples

arXiv

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arXiv 2023年

作者： Wang, Jinwei Wu, Hao Wang, Haihua Zhang, Jiawei Luo, Xiangyang Ma, Bin Nanjing University of Information Science and Technology China State Key Laboratory of Mathematical Engineering and Advanced Computing China Qilu University of Technology China

The vulnerability of Deep Neural Networks (DNNs) to adversarial examples has been confirmed. Existing adversarial defenses primarily aim at preventing adversarial examples from attacking DNNs successfully, rather than preventing their generation. If the generation of adversarial examples is unregulated, images within reach are no longer secure and pose a threat to non-robust DNNs. Although gradient obfuscation attempts to address this issue, it has been shown to be circumventable. Therefore, we propose a novel adversarial defense mechanism, which is referred to as immune defense and is the example-based pre-defense. This mechanism applies carefully designed quasi-imperceptible perturbations to the raw images to prevent the generation of adversarial examples for the raw images, and thereby protecting both images and DNNs. These perturbed images are referred to as Immune Examples (IEs). In the white-box immune defense, we provide a gradient-based and an optimization-based approach, respectively. Additionally, the more complex black-box immune defense is taken into consideration. We propose Masked Gradient Sign Descent (MGSD) to reduce approximation error and stabilize the update to improve the transferability of IEs and thereby ensure their effectiveness against black-box adversarial attacks. The experimental results demonstrate that the optimization-based approach has superior performance and better visual quality in white-box immune defense. In contrast, the gradient-based approach has stronger transferability and the proposed MGSD significantly improve the transferability of baselines. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep neural networks

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Publicly Verifiable Private Set Intersection from Homomorphic Encryption 8th

Publicly Verifiable Private Set Intersection from Homomorph...

引用

8th International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2022

作者： Jiang, Yuting Wei, Jianghong Pan, Jing Xidian University Xi’an710071 China State Key Laboratory of Mathematical Engineering and Advanced Computing PLA Strategic Support Force Information Engineering University Zhengzhou450001 China Guangzhou Institute of Technology Xidian University Guanzhou510555 China

ISBN: (纸本)9789811972416

Private Set Intersection (PSI) enables two mistrusting parties to securely evaluate the intersection of their private inputs, without revealing any additional information. With its wide application in privacy protection, it is required to ensure the correctness of the evaluation, especially in conventional client-server setting (also known as unbalanced PSI). Unfortunately, most existing work cannot verify the integrity of the data and the correctness of the evaluation. In this paper, we propose a new publicly verifiable private set intersection protocol in the malicious setting, based on oblivious pseudo-random function (OPRF), fully homomorphic encryption (FHE), and verifiable computation (VC). The key tool to obtain our new protocol is a new publicly verifiable inner product computation on encrypted data. The protocol supports public verification for computation correctness and integrity under preserving privacy with less round number (only requiring 2 rounds), allows batching technique under Residue Number System (RNS). That is used for enhancing the FHE. Also, we implement our protocol, and the result is close to the most effective unbalanced PSI. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Numbering systems

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