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4th International Conference on Data Mining, Communications and Information Technology, DMCIT 2020

作者： He, Kang Liu, Long Lu, Dong-Zhe Zhu, Yuefei State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China Information Engineering University Zhengzhou450001 China

PDF files are adopted for launching cyberattacks because of their popularity and the increasing number of relative vulnerabilities. Machine learning algorithms are developed to detect the maliciousness of PDF files. As the exploits of new vulnerabilities occur, the assumption that the training data and the test data share the same distribution does not hold and the ability of origin model to detect exploits of new vulnerabilities weakens gradually. In a real environment, it is very difficult to obtain numerous samples of exploits with the same CVE. and the machine learning models are difficult to be improved by retraining. Virtual sample generation could be used to generate sufficient virtual samples by small sample sets to improve the generalization of the existing model. A new VSG algorithm based on prior knowledge is proposed in this paper, which performs better than other VSG algorithms in improving the detection on exploits of new vulnerabilities. © Published under licence by IOP Publishing Ltd.

关键词： Learning algorithms

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A Novel Deep Learning Approach Featuring Graph-Based Algorithm for Cell Segmentation and Tracking

A Novel Deep Learning Approach Featuring Graph-Based Algorit...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Zhao, Keliang Niyogisubizo, Jovial Xiao, Linxia Pan, Yi Wei, Dongqing Rosiyadi, Didi Wei, Yanjie Chinese Academy of Sciences Shenzhen Key Laboratory of Intelligent Bioinformatics and Center for High Performance Computing Shenzhen Institute of Advanced Technology Shenzhen518055 China Chinese Academy of Sciences College of Computer Science and Control Engineering Shenzhen Institutes of Advanced Technology Shenzhen518055 China Shanghai Jiao Tong University State Key Laboratory of Microbial Metabolism School of Life Sciences and Biotechnology Shanghai200240 China National Research and Innovation Agency Research Center for Artificial Intelligence and Cybersecurity Bandung Indonesia

ISBN: (纸本)9798350337488

The precise segmentation and tracking of cells in microscopy image sequences play a pivotal role in biomedical research, facilitating the study of tissue, organ, and organism development. However, manual segmentation and tracking of cells is time-consuming and often require professional experiences. Besides, segmenting cells in the images with a low signal-to-noise ratio remains difficult. While deep learning (DL) has become a common method for cell segmentation, few DL- based methods address concurrent cell segmentation and tracking. In this paper, we propose a novel DL approach featuring graph-based tracking for cell segmentation and tracking in microscopy images. We combine Deeplabv3+ for semantic segmentation and ResNet50 for enhanced feature extraction, enabling comprehensive cell detection and instance segmentation. Post-processing, involving non-maxima suppression and outlier detection, refines predictions and produces final segmentation. The tracking method is based on the relative position of graph nodes to track segmented cells, encompassing cell division and apoptosis. We conduct our experiments on the induced pluripotent stem (iPS) cell datasets, and the results show that the segmentation and tracking performance of our method yields superior performance compared to the benchmark models. More specifically, our approach achieved DET values of 0.955 and 0.913, TRA values of 0.951 and 0.906, and SEG values of 0.690 and 0.665 on two iPS dataset videos, respectively. Additionally, the performance assessment encompasses four real microscopy datasets from the Cell Tracking Challenge (CTC). Our method greatly reduces the cost of manual labeling and labor-intensive costs. © 2023 IEEE.

关键词： cell segmentation cell tracking deep learning Deeplabv3+ instance segmentation iPS cell reprogramming

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An overview on the designs of distributed observers in LTI multi-agent systems

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Science China(Technological Sciences) 2021年第11期64卷 2337-2346页

作者： PEI YingQing GU HaiBo LIU KeXin LU JinHu Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain ComputingBeihang UniversityBeijing 100191China

With the rapid development of information technologies and cloud computing, sensor networks play an increasingly important role in our society. Over the past few decades, distributed observer theory has attracted unprecedented attention due to its wide potential applications in different areas. Meanwhile, various approaches and algorithms have been proposed and investigated. The design of distributed observers is one of the frontier topics of system and control research, which has the significant theoretical values and broad application prospects. This paper attempts to review the representative models and the corresponding approaches for distributed observer design in linear time-invariant(LTI) systems. Firstly, the research backgrounds and main advances of distributed observer designs are briefly reviewed. Then, recent results of distributed observer designs for discrete-time and continuous-time LTI multi-agent systems(MASs) are introduced in detail, respectively. Finally, the prospects and the future work directions of the design of distributed observers are put forward. The main purpose of this paper is to promote the emerging topic on the designs of distributed observers, with focuses on the interdisciplinary interest from technological sciences.

关键词： multi-agent system linear time-invarient system distributed observer consensus

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Unconditionally optimal convergence of an energy-conserving and linearly implicit scheme for nonlinear wave equations

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Science China Mathematics 2022年第8期65卷 1731-1748页

作者： Waixiang Cao Dongfang Li Zhimin Zhang School of Mathematical Sciences Beijing Normal UniversityBeijing 100875China School of Mathematics and Statistics Huazhong University of Science and TechnologyWuhan 430074China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and TechnologyWuhan 430074China Beijing Computational Science Research Center Beijing 100193China Department of Mathematics Wayne State UniversityDetroitMI 48202USA

In this paper,we present and analyze an energy-conserving and linearly implicit scheme for solving the nonlinear wave *** error estimates in time and superconvergent error estimates in space are established without certain time-step *** key is to estimate directly the solution bounds in the H-norm for both the nonlinear wave equation and the corresponding fully discrete scheme,while the previous investigations rely on the temporal-spatial error splitting *** examples are presented to confirm energy-conserving properties,unconditional convergence and optimal error estimates,respectively,of the proposed fully discrete schemes.

关键词： scalar auxiliary variable wave equations stability error estimate superconvergence

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Towards Comprehensively Understanding the Run-time Security of Programmable Logic Controllers: A 3-year Empirical Study

arXiv

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arXiv 2022年

作者： Ma, Rongkuan Wei, Qiang Wang, Jingyi Zhu, Shunkai Ji, Shouling Cheng, Peng Jia, Yan Wang, Qingxian State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Zhengzhou450001 China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310000 China College of Cyber Science Nankai University Tianjin China

Programmable Logic Controllers (PLCs) are the core control devices in Industrial Control Systems (ICSs), which control and monitor the underlying physical plants such as power grids. PLCs were initially designed to work in a trusted industrial network, which however can be brittle once deployed in an Internet-facing (or penetrated) network. Yet, there is a lack of systematic empirical analysis of the run-time security of modern real-world PLCs. To close this gap, we present the first large-scale measurement on 23 off-the-shelf PLCs across 13 leading vendors. We find many common security issues and unexplored implications that should be more carefully addressed in the design and implementation. To sum up, the unsupervised logic applications can cause system resource/privilege abuse, which gives adversaries new means to hijack the control flow of a runtime system remotely (without exploiting memory vulnerabilities);2) the improper access control mechanisms bring many unauthorized access implications;3) the proprietary or semi-proprietary protocols are fragile regarding confidentiality and integrity protection of run-time data. We empirically evaluated the corresponding attack vectors on multiple PLCs, which demonstrates that the security implications are severe and broad. Our findings were reported to the related parties responsibly, and 20 bugs have been confirmed with 7 assigned CVEs. Copyright © 2022, The Authors. All rights reserved.

关键词： Programmable logic controllers

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Anti-reconnaissance Model of Host Fingerprint Based on Virtual Node 4

Anti-reconnaissance Model of Host Fingerprint Based on Virtu...

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4th International Conference on Data Mining, Communications and Information Technology, DMCIT 2020

作者： Zhang, Tao Lu, Bin Li, Ding He, Kang Zhu, Yuefei State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China Information Engineering University Zhengzhou450001 China

Aiming at the problem of insufficient defense ability of fingerprint detection, the anti-reconnaissance model of host fingerprint based on virtual node is proposed. The model constructs periodically reconfigurable virtual nodes, dynamically camouflages the fingerprint information of the host to deceive the detector, and redirect attack traffic targeting virtual nodes to honeypots that can capture and analyze attack behavior. Honeypot, as an active defense technology, can effectively improve the model's defense capabilities. This paper introduces probabilistic models for the defense model to provide a deeper understanding of the theoretical effect their parameters have for cybersecurity, which quantifies the impact of different parameters on the probability of attack success, such as the number of probes, number of honeypot mapping rules, the virtual node deception rate, the honeypot detection rate and allowable losses. Furthermore, our prototype system using Software Defined Network (SDN) and Data Plane Development Kit (DPDK) verifies the effectiveness of the model against reconnaissance. © Published under licence by IOP Publishing Ltd.

关键词： Network security

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Dynamic Nonreciprocity with a Kerr Nonlinear Resonator

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Chinese Physics Letters 2022年第12期39卷 28-34页

作者： Rui-Kai Pan Lei Tang keyu Xia Franco Nori College of Engineering and Applied Sciences National Laboratory of Solid State Microstructuresand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210093China College of Physics and Electronic Engineering Sichuan Normal UniversityChengdu 610101China Jiangsu Key Laboratory of Artificial Functional Materials Nanjing UniversityNanjing 210023China Shishan Laboratory Suzhou Campus of Nanjing UniversitySuzhou 215000China RIKEN Quantum Computing Center RIKEN Cluster for Pioneering ResearchWako-shiSaitama 351-0198Japan Physics Department The University of MichiganAnn ArborMichigan 48109-1040USA

On-chip optical nonreciprocal devices are vital components for integrated photonic systems and scalable quantum information *** optical isolators and circulators have attracted considerable attention because of their fundamental interest and their important advantages in integrated photonic ***,optical nonreciprocal devices based on Kerr or Kerr-like nonlinearity are subject to dynamical reciprocity when the forward and backward signals coexist simultaneously in a nonlinear ***,we theoretically propose a method for realizing on-chip nonlinear isolators and circulators with dynamic *** nonreciprocity is achieved via the chiral modulation on the resonance frequency due to coexisting self-and cross-Kerr nonlinearities in an optical ring *** work showing dynamic nonreciprocity with a Kerr nonlinear resonator can be an essential step toward integrated optical isolation.

关键词： Nonlinear nonlinear reciprocal

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A secure spectrum auction scheme without the trusted party based on the smart contract

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Digital Communications and Networks 2021年第2期7卷 223-234页

作者： Jiaqi Wang Ning Lu Qingfeng Cheng Lu Zhou Wenbo Shi School of Computer Science and Engineerings Northeastern University Shenyang 110004China School of Computer Science and Technology Xidian UniversityXi'anChina Strategic Support Force Information Engineering University Zhengzhou450001China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001China Division of Computer Science University ofAizuAizu-WakamatsuJapan School of Computer and Communication Engineering Nordieastem UniversityQinhuangdao066004China

With the development of communication 5G networks and technologies,spectrum resources are increasingly *** scarcity of the spectrum resource makes market-driven spectrum auction become an important means of spectrum allocation,and due to the complexity of the network environment,the security of spectrum auctions can not be *** existing secure spectrum auction schemes introduce a semi-honest agent to complete spectrum ***,the hypothetical semi-honest model does not guarantee the security of spectnim auction in the actual application scenario,which may lead to potential security threats:the agent may reveal the privacy of bidders,agent or auctioneer may collude with the bidder to manipulate the spectrum auction,and so *** this paper,a secure spectrum auction scheme without a trusted party is proposed based on the smart contract technology,and the smart contract written into the blockchain replaces the traditional semi-honest agent to cooperate with the auctioneer server to complete the *** order to ensure the security of our scheme,a secure spectrum auction protocol is designed,in which the Software Guard Extensions(SGX)technology and Paillier cryptosystem are used to protect the privacy of *** verification is provided in our protocol by using extensive Pedersen commitment,which prevents the auctioneer server and the bidder from colluding with each other and verifies group bid sum ***,the security analysis is given to propose several types of attacks that can be ***,theoretical analysis and simulation experiments of our protocol are also provided.

关键词： 5g Secure spectrum auction Bidders'bids'privacy Smart contract Public verification

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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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Coarse-to-Fine Proposal Refinement Framework for Audio Temporal Forgery Detection and Localization

arXiv

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arXiv 2024年

作者： Wu, Junyan Lu, Wei Luo, Xiangyang Yang, Rui Wang, Qian Cao, Xiaochun School of Computer Science and Engineering Sun Yat-sen University Guangzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Alibaba Group Hangzhou China School of Cyber Science and Engineering Wuhan University Wuhan China School of Cyber Science and Technology Shenzhen Campus of Sun Yat-sen University Shenzhen China

MSC Codes 68T07, 68T10Recently, a novel form of audio partial forgery has posed challenges to its forensics, requiring advanced countermeasures to detect subtle forgery manipulations within long-duration audio. However, existing countermeasures still serve a classification purpose and fail to perform meaningful analysis of the start and end timestamps of partial forgery segments. To address this challenge, we introduce a novel coarse-to-fine proposal refinement framework (CFPRF) that incorporates a frame-level detection network (FDN) and a proposal refinement network (PRN) for audio temporal forgery detection and localization. Specifically, the FDN aims to mine informative inconsistency cues between real and fake frames to obtain discriminative features that are beneficial for roughly indicating forgery regions. The PRN is responsible for predicting confidence scores and regression offsets to refine the coarse-grained proposals derived from the FDN. To learn robust discriminative features, we devise a difference-aware feature learning (DAFL) module guided by contrastive representation learning to enlarge the sensitive differences between different frames induced by minor manipulations. We further design a boundary-aware feature enhancement (BAFE) module to capture the contextual information of multiple transition boundaries and guide the interaction between boundary information and temporal features via a cross-attention mechanism. Extensive experiments show that our CFPRF achieves state-of-the-art performance on various datasets, including LAV-DF, ASVS2019PS, and HAD. Copyright © 2024, The Authors. All rights reserved.

关键词： Machine learning

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