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Machine Learning Security Defense Algorithms Based on Metadata Correlation Features

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computers, Materials & Continua 2024年第2期78卷 2391-2418页

作者： Ruchun Jia Jianwei Zhang Yi Lin college of computer Science Sichuan UniversityChengdu610065China

With the popularization of the Internet and the development of technology,cyber threats are increasing day by *** such as malware,hacking,and data breaches have had a serious impact on *** network security environment in the era of big data presents the characteristics of large amounts of data,high diversity,and high real-time *** security defense methods and tools have been unable to cope with the complex and changing network security *** paper proposes a machine-learning security defense algorithm based on metadata association *** control over unauthorized users through privacy,integrity,and *** user model is established and the mapping between the user model and the metadata of the data source is *** analyzing the user model and its corresponding mapping relationship,the query of the user model can be decomposed into the query of various heterogeneous data sources,and the integration of heterogeneous data sources based on the metadata association characteristics can be *** and classify customer information,automatically identify and perceive sensitive data,build a behavior audit and analysis platform,analyze user behavior trajectories,and complete the construction of a machine learning customer information security defense *** experimental results show that when the data volume is 5×103 bit,the data storage integrity of the proposed method is 92%.The data accuracy is 98%,and the success rate of data intrusion is only 2.6%.It can be concluded that the data storage method in this paper is safe,the data accuracy is always at a high level,and the data disaster recovery performance is *** method can effectively resist data intrusion and has high air traffic control *** can not only detect all viruses in user data storage,but also realize integrated virus processing,and further optimize the security defense effect of user big data.

关键词： Data-oriented architecture metadata correlation features machine learning security defense data source integration

Image encryption algorithm based on multiple chaotic systems and improved Joseph block scrambling

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Chinese Physics B 2024年第10期33卷 248-257页

作者： Dingkang Mou Yumin Dong college of computer and Information Science Chongqing Normal UniversityChongqing 400047China

With the rapid development of digital information technology,images are increasingly used in various *** ensure the security of image data,prevent unauthorized tampering and leakage,maintain personal privacy,and protect intellectual property rights,this study proposes an innovative color image encryption ***,the Mersenne Twister algorithm is utilized to generate high-quality pseudo-random numbers,establishing a robust basis for subsequent ***,two distinct chaotic systems,the autonomous non-Hamiltonian chaotic system and the tentlogistic-cosine chaotic mapping,are employed to produce chaotic random *** chaotic sequences are used to control the encoding and decoding process of the DNA,effectively scrambling the image ***,the complexity of the encryption process is enhanced through improved Joseph block *** experimental verification,research,and analysis,the average value of the information entropy test data reaches as high as ***,the average value of the number of pixels change rate(NPCR)test data is 99.6101%,which closely approaches the ideal value of 99.6094%.This algorithm not only guarantees image quality but also substantially raises the difficulty of decryption.

关键词： mersenne twister algorithm DNA coding confusion pixel XOR operation improved Joseph block scrambling

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Developing a Model for Parkinson’s Disease Detection Using Machine Learning Algorithms

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computers, Materials & Continua 2024年第6期79卷 4945-4962页

作者： Naif Al Mudawi Department of computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia

Parkinson’s disease(PD)is a chronic neurological condition that progresses over *** start to have trouble speaking,writing,walking,or performing other basic skills as dopamine-generating neurons in some brain regions are injured or *** patient’s symptoms become more severe due to the worsening of their signs over *** this study,we applied state-of-the-art machine learning algorithms to diagnose Parkinson’s disease and identify related risk *** research worked on the publicly available dataset on PD,and the dataset consists of a set of significant characteristics of *** aim to apply soft computing techniques and provide an effective solution for medical professionals to diagnose PD *** research methodology involves developing a model using a machine learning *** the model selection,eight different machine learning techniques were adopted:Namely,Random Forest(RF),Decision Tree(DT),Support Vector Machine(SVM),Naïve Bayes(NB),Light Gradient Boosting Machine(LightGBM),K-Nearest Neighbours(KNN),Extreme Gradient Boosting(XGBoost),and Logistic Regression(LR).Subsequently,the concentrated models were validated through 10-fold Cross-Validation and Receiver Operating Characteristic(ROC)—Area Under the Curve(AUC).In addition,GridSearchCV was utilised to measure each algorithm’s best parameter;eventually,the models were trained through the hyperparameter tuning *** 98%accuracy,LightGBM had the highest accuracy in this ***,KNN,and SVM came in second with 96%***,the performance scores of NB and LR were recorded to be 76%and 83%,*** is to be mentioned that after applying 10-fold cross-validation,the average performance score of LightGBM accounted for 93%.At the same time,the percentage of ROC-AUC appeared at 0.92,which indicates that this LightGBM model reached a satisfactory ***,we extracted meaningful insights and figured out potential gaps on top of *** extracting meaningful in

关键词： Light GBM cross-validation ROC-AUC Parkinson’s disease(PD) SVM and XGBoost

APF-GAN:Exploring asymmetric pre-training and fine-tuning strategy for conditional generative adversarial network

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Computational Visual Media 2024年第1期10卷 187-192页

作者： Yuxuan Li Lingfeng Yang Xiang Li college of computer Science Nankai UniversityTianjinChina School of computer Science and Engineering Nanjing University of Science and TechnologyNanjingChina

The use of generative adversarial network(GAN)-based models for the conditional generation of image semantic segmentation has shown promising results in recent ***,there are still some limitations,including limited diversity of image style,distortion of detailed texture,unbalanced color tone,and lengthy training *** address these issues,we propose an asymmetric pre-training and fine-tuning(APF)-GAN model.

关键词： tuning network asymmetric

Two-layer Lagrange-based relay network topology and trajectory design for solar system explorations

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Science China(Information Sciences) 2024年第6期67卷 342-358页

作者： Jun CAO Jian JIAO Hao LIU Rongxing LU Qinyu ZHANG Guangdong Provincial Key Laboratory of Aerospace communication and Networking Technology Harbin Institute of Technology (Shenzhen) Faculty of computer Science (FCS) University of New Brunswick

Exploration targeting outer planets and even the edge of the solar system is an emerging direction for the deep-space exploration in the next decades. To address this challenge, a novel two-layer Lagrangebased relay network topology is proposed in this study. Specifically, we utilize the Sun-Mars and Sun-Saturn Lagrange points(LPs) L4 and L5 to build a two-layer backbone relay network, which ensures continuous and high-efficiency communication capability for the exploration of the solar system. Furthermore, we utilize the planetary gravity assist and design the transfer trajectory of backbone relays with the help of planetary celestial body motion equations and Kepler's laws. Moreover, we conduct link budget analysis for multihop relay transmission under Gamma-Gamma distribution, shadowed Rician fading, and additive white Gaussian noise channels in several typical exploration scenarios and validate that the LP relays can effectively support future deep-space exploration missions.

关键词： deep-space communication Lagrangian points backbone relay network transfer trajectory relay selection

What can we learn from quality assurance badges in open-source software?

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Science China(Information Sciences) 2024年第4期67卷 146-163页

作者： Feng LI Yiling LOU Xin TAN Zhenpeng CHEN Jinhao DONG Yang LI Xuanzhi WANG Dan HAO Lu ZHANG MoE Key Lab of HCST School of Computer SciencePeking University Department of computer Science Purdue University School of computer Science & Engineering Beihang University(BUAA) Department of computer Science University College London(UCL)

In the development of open-source software(OSS), many developers use badges to give an overview of the software and share some key features/metrics conveniently. Among various badges, quality assurance(QA) badges make up a large proportion and are the most prevalent because QA is of vital importance in software development, and ineffective QA may lead to anomalies or defects. In this paper, we focus on QA badges in open-source projects, which present quality assurance information directly and instantly,and aim to produce some interesting findings and provide practical implications. We collect and analyze 100000 projects written in popular programming languages from GitHub and conduct a comprehensive empirical study both inside and outside QA badges. Inside QA badges, we build a category classification for all QA badges based on the properties they focus on, which shows the types of QA badges developers use. Then,we analyze the frequency of the properties that QA badges focus on, and property combinations, too, which present their use status. We find that QA badges focus on various properties while developers give different preferences to different properties. The use status also differs between different programming languages. For example, projects written in C focus on Security to a great extent. Our findings also provide implications for developers and badge providers. Outside QA badges, we conduct a correlation analysis between QA badges and some software metrics that have potential relationships with code quality, contribution quality, and popularity. We find that QA badges have statistically significant correlations with various software metrics.

关键词： quality assurance badge open-source software code quality empirical study

Intelligent reflecting surfaces-assisted millimeter wave communication:Channel estimation based on deep learning

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The Journal of China Universities of Posts and Telecommunications 2024年第1期31卷 49-56页

作者： Kang Xiaofei Wang Tian Liang Xian college of communication and Information Engineering Xi'an University of Science and TechnologyXi'an 710600China

In response to the challenge posed by the complexity of the system and the difficulty in obtaining accurate channel state information(CSI)for millimeter wave communication assisted by intelligent reflecting surfaces(IRS),we propose a deep learning-based channel estimation *** proposed scheme employs a hybrid active/passive IRS architecture,wherein the least square(LS)algorithm is initially utilized to acquire the channel estimate from the active ***,this estimation is interpolated to obtain a preliminary channel estimation and ultimately refined into an accurate estimate of the channel using the channel super-resolution convolutional neural network(Chan-SRCNN)deep learning *** simulation results demonstrate that the proposed scheme surpasses LS,orthogonal matching pursuit(OMP),synchronous OMP(SOMP),and deep neural network(DNN)channel estimation algorithms in terms of normalized mean squared error(NMSE)performance,thereby validating the feasibility of the proposed approach.

关键词： intelligent reflecting surface millimeter wave channel estimation deep learning

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Drug-Target Interactions Prediction Based on Signed Heterogeneous Graph Neural Networks

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Chinese Journal of Electronics 2024年第1期33卷 231-244页

作者： Ming CHEN Yajian JIANG Xiujuan LEI Yi PAN Chunyan JI Wei JIANG college of Information Science and Engineering Hunan Normal University School of computer Science Shaanxi Normal University Faculty of computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences computer Science Department BNU-HKBU United International College

Drug-target interactions(DTIs) prediction plays an important role in the process of drug *** computational methods treat it as a binary prediction problem, determining whether there are connections between drugs and targets while ignoring relational types information. Considering the positive or negative effects of DTIs will facilitate the study on comprehensive mechanisms of multiple drugs on a common target, in this work, we model DTIs on signed heterogeneous networks, through categorizing interaction patterns of DTIs and additionally extracting interactions within drug pairs and target protein pairs. We propose signed heterogeneous graph neural networks(SHGNNs), further put forward an end-to-end framework for signed DTIs prediction, called SHGNN-DTI,which not only adapts to signed bipartite networks, but also could naturally incorporate auxiliary information from drug-drug interactions(DDIs) and protein-protein interactions(PPIs). For the framework, we solve the message passing and aggregation problem on signed DTI networks, and consider different training modes on the whole networks consisting of DTIs, DDIs and PPIs. Experiments are conducted on two datasets extracted from Drug Bank and related databases, under different settings of initial inputs, embedding dimensions and training modes. The prediction results show excellent performance in terms of metric indicators, and the feasibility is further verified by the case study with two drugs on breast cancer.

关键词： Drugs Training Proteins Measurement Message passing Prediction methods Graph neural networks

A Distributed Adaptive Second-Order Latent Factor Analysis Model

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IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2343-2345页

作者： Jialiang Wang Weiling Li Xin Luo the School of computer Science and Technology Dongguan University of Technology the college of computer and Information Science Southwest University

Dear Editor,This letter presents a distributed adaptive second-order latent factor(DAS) model for addressing the issue of high-dimensional and incomplete data representation. Compared with first-order optimizers, a second-order optimizer has stronger ability in approaching a better solution when dealing with the non-convex optimization problems, thus obtaining better performance in extracting the latent factors(LFs) well representing the known information from high-dimensional and incomplete data.

关键词： Particle swarm optimization (PSO)