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Manhattan-based k-member clustering and enhanced rabbit optimization algorithm for k-anonymization in social network

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Multimedia Tools and Applications 2024年第30期83卷 74739-74756页

作者： Sivasankari, K. Maheswari, K. M. Uma Department of computer science and engineering SRM Institute of Science and Technology Ramapuram Chennai India Department of computing technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur India

Online social networks are becoming more and more popular, according to recent trends. The user's primary concern is the secure preservation of their data and privacy. A well-known method for preventing individual identity in publicly accessible datasets is K-anonymization. Existing anonymity techniques' primary drawback is that they're susceptible to similarity and attribute disclosure attacks. Furthermore, a large amount of data has been lost in the given database. To address this limitation, the proposed model integrated an anonymizing algorithm with Manhattan-based k-member clustering and an enhanced rabbit optimization algorithm (MKCAEROA). The Manhattan distance-based k member (MKCA) clustering algorithm is employed in this case to cluster the initial database. The resulting clusters are then further optimized, and the original database is made anonymous, using the enhanced rabbit optimization algorithm (EROA). In the suggested model, EROA is included to satisfy the specified anonymity constraints while concurrently minimizing the clustering error rate and the generated information loss. When compared to existing approaches, the experimental results demonstrate that the suggested method provides the highest clustering accuracy with the least amount of information loss. The MATLAB workbench will be used to implement the suggested model. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Database systems

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ScanSavant: Malware Detection for Android Applications with Explainable AI

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2024年第19期18卷 171-181页

作者： Navaneethan, S. Udhaya Kumar, S. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Tamil Nadu Chennai India

Mobile devices face SQL injection, malware, and web-based threats. Current solutions lack real-time detection. This paper introduces an Android app with advanced algorithms for real-time threat scanning. During testing, our application detected 94% of SQL injection attempts, outperforming the 86% average detection rate in similar studies. For malware analysis, it achieved a 97% detection accuracy on a dataset of infected files, higher than the industry standard of 93%. Additionally, our app can detect 85 malware variants and assign 15 attributes (***.8, ***, ***, ***, ***, ***, ***-2017-0143, ***, ***, Backdoor. DarkComet, ***, ***, ***, ***32. Necurs, and ***) to some malwares, providing detailed analysis for better threat management. The application effectively scans both EXE and APK files, ensuring com-prehensive protection. When assessing website links, the application identified security risks with 96% accuracy, demonstrating its capability in managing web-based threats. This app detects SQL injections, analyses malware, and assesses website security, bolstering cyber defence with user-friendly features and top-notch threat mitigation. © 2024, International Federation of Engineering Education Societies (IFEES). All rights reserved.

关键词： Android malware

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RESEARCH ON INTELLIGENT LIGHTING CONTROL SYSTEM BASED ON FIBER OPTIC IoT

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical Engineering and computer science 2024年第1期86卷 167-178页

作者： Liu, Zhao Yu, Chunrong Yu, Aiwen Liu, Dan School of Computer Science and Engineering Cangzhou Normal University China College of Intelligence and Computing Tianjin University China

To achieve intelligent lighting with multiple targets on a large scale and improve the energy utilization rate of the system, we design an intelligent lighting control system based on the fiber optic Internet of Things (IoT) and propose a neural network algorithm based on deep combination. After learning and analyzing the test data of fiber optic sensing networks, it provides a threshold solution method for selecting lighting equipment based on target location in a large range of lighting areas. Based on the neural network structure, it analyzes the lighting state control process with fiber optic IoT echo response as the input layer. In the lighting target recognition test, vehicles and pedestrians were tested separately. The results show that the maximum response voltages of the vehicle after amplification are 3.47V and 0.91V, respectively. The maximum response voltages of the pedestrian after amplification are 1.81V and 0.65V, respectively. The spectral distribution can distinguish the motion states of pedestrians and vehicles. The response amplitude of the vehicle is strong and the delay is long. The amplitude intensity of pedestrian movement is small and the delay is short. In the illumination experiment, according to the distribution changes of P1-P4, the target is always at the optimal illumination position in the illumination area. Its light energy utilization rate is the highest, which means its electrical energy utilization rate is also the best. It has certain advantages for intelligent control of large-scale lighting. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Internet of things

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Automated detection of sugarcane crop lines from UAV images using deep learning

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Information Processing in Agriculture 2024年第3期11卷 385-396页

作者： Joao Batista Ribeiro Renato Rodrigues da Silva Jocival Dantas Dias Mauricio Cunha Escarpinati Andre Ricardo Backes School of Computer Science-Federal University of Uberlandia UberlandiaMGBrazil Department of Computing-Federal University of Sao Carlos Sao CarlosSPBrazil

UAVs(Unmanned Aerial Vehicles)have become increasingly popular in the agricultural sector,promoting and enabling the application of aerial image monitoring in both the scientific and business *** captured by UAVs are fundamental for precision farming *** enable us do a better crop planning,input estimates,early identification and correction of sowing failures,more efficient irrigation systems,among other *** all these activities deal with low or medium altitude images,automated identification of crop lines plays a crucial role improving these *** address the problem of detecting and segmenting crop *** use a Convolutional Neural Network to segment the images,labeling their regions in crop lines or unplanted *** also evaluated three traditional semantic networks:U-Net,LinkNet,and *** compared each network in four segmentation datasets provided by an *** also assessed whether the network’s output requires a post-processing step to improve the *** demonstrate the efficiency and feasibility of these networks in the proposed task.

关键词： Crop line Aerial Images CNN UAV Precision agriculture

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Method and Practice of Trusted Embedded computing and Data Transmission Protection Architecture Based on Android

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Chinese Journal of Electronics 2024年第3期33卷 623-634页

作者： Yichuan WANG Wen GAO Xinhong HEI Yanning DU School of Computer Science and Engineering Xi'an University of Technology Shaanxi Key Laboratory for Network Computing and Security Technology

In recent years,the rapid development of Internet technology has constantly enriched people's daily life and gradually changed from the traditional computer terminal to the mobile *** with it comes the security problems brought by the mobile *** for Android system,due to its open source nature,malicious applications continue to emerge,which greatly threatens the data security of ***,this paper proposes a method of trusted embedded static measurement and data transmission protection architecture based on Android to reduce the risk of data leakage in the process of terminal storage and *** conducted detailed data and feasibility analysis of the proposed method from the aspects of time consumption,storage overhead and *** experimental results show that this method can detect Android system layer attacks such as self-booting of the malicious module and improve the security of data encryption and transmission process *** with the native system,the additional performance overhead is small.

关键词： TrustZone Static measurement Data leakage Android

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Optimizing Image Retrieval in Cloud Servers with TN-AGW: A Secure and Efficient Approach

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Journal of The Institution of Engineers (India): Series B 2025年第2期106卷 459-473页

作者： Ponnuviji, N.P. Nirmala, G. Kokila, M. L. Sworna Priyadharshini, S. Indra Department of Computer Science and Engineering RMK College of Engineering and Technology Puduvoyal Thiruvallur India Department of Computer Science and Engineering RMD Engineering College Chennai India Department of Computing Technologies School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Tamil Nādu Kattankulathur Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India

The increasing use of cloud-based image storage and retrieval systems has made ensuring security and efficiency crucial. The security enhancement of image retrieval and image archival in cloud computing has received considerable attention in transmitting data and ensuring data confidentiality among cloud servers and users. Various traditional image retrieval techniques regarding security have developed in recent years but they do not apply to large-scale environments. This paper introduces a new approach called Triple network-based adaptive grey wolf (TN-AGW) to address these challenges. The TN-AGW framework combines the adaptability of the Grey Wolf Optimization (GWO) algorithm with the resilience of Triple Network (TN) to enhance image retrieval in cloud servers while maintaining robust security measures. By using adaptive mechanisms, TN-AGW dynamically adjusts its parameters to improve the efficiency of image retrieval processes, reducing latency and utilization of resources. However, the image retrieval process is efficiently performed by a triple network and the parameters employed in the network are optimized by Adaptive Grey Wolf (AGW) optimization. Imputation of missing values, Min–Max normalization, and Z-score standardization processes are used to preprocess the images. The image extraction process is undertaken by a modified convolutional neural network (MCNN) approach. Moreover, input images are taken from datasets such as the Landsat 8 dataset and the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset is employed for image retrieval. Further, the performance such as accuracy, precision, recall, specificity, F1-score, and false alarm rate (FAR) is evaluated, the value of accuracy reaches 98.1%, the precision of 97.2%, recall of 96.1%, and specificity of 917.2% respectively. Also, the convergence speed is enhanced in this TN-AGW approach. Therefore, the proposed TN-AGW approach achieves greater efficiency in image retrieving than other existing

关键词： Extraction

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A Comprehensive Study of Resource Provisioning and Optimization in Edge computing

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computers, Materials & Continua 2025年第6期83卷 5037-5070页

作者： Sreebha Bhaskaran Supriya Muthuraman Department of Computer Science and Engineering Amrita School of ComputingBengaluru560035Amrita Vishwa VidyapeethamIndia

Efficient resource provisioning,allocation,and computation offloading are critical to realizing lowlatency,scalable,and energy-efficient applications in cloud,fog,and edge *** its importance,integrating Software Defined Networks(SDN)for enhancing resource orchestration,task scheduling,and traffic management remains a relatively underexplored area with significant innovation *** paper provides a comprehensive review of existing mechanisms,categorizing resource provisioning approaches into static,dynamic,and user-centric models,while examining applications across domains such as IoT,healthcare,and autonomous *** survey highlights challenges such as scalability,interoperability,and security in managing dynamic and heterogeneous *** exclusive research evaluates how SDN enables adaptive policy-based handling of distributed resources through advanced orchestration ***,proposes future directions,including AI-driven optimization techniques and hybrid *** addressing these emerging opportunities,thiswork serves as a foundational reference for advancing resource management strategies in next-generation cloud,fog,and edge computing *** survey concludes that SDN-enabled computing environments find essential guidance in addressing upcoming management opportunities.

关键词： Cloud computing edge computing fog computing resource provisioning resource allocation computation offloading optimization techniques software defined network

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SmartEagleEye:A Cloud-Oriented Webshell Detection System Based on Dynamic Gray-Box and Deep Learning

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Tsinghua science and Technology 2024年第3期29卷 766-783页

作者： Xin Liu Yingli Zhang Qingchen Yu Jiajun Min Jun Shen Rui Zhou Qingguo Zhou School of Information Science and Engineering Lanzhou UniversityLanzhou 730000China College of Computer Science and Technology Zhejiang UniversityHangzhou 310058China School of Computing and Information Technology University of WollongongWollongong 2500Australia

Compared with traditional environments,the cloud environment exposes online services to additional vulnerabilities and threats of cyber attacks,and the cyber security of cloud platforms is becoming increasingly prominent.A piece of code,known as a Webshell,is usually uploaded to the target servers to achieve multiple *** Webshell attacks has become a hot spot in current ***,the traditional Webshell detectors are not built for the cloud,making it highly difficult to play a defensive role in the cloud ***,a Webshell detection system based on deep learning that is successfully applied in various scenarios,is proposed in this *** system contains two important components:gray-box and neural network *** gray-box analyzer defines a series of rules and algorithms for extracting static and dynamic behaviors from the code to make the decision *** neural network analyzer transforms suspicious code into Operation Code(OPCODE)sequences,turning the detection task into a classification *** experiment results show that SmartEagleEye achieves an encouraging high detection rate and an acceptable false-positive rate,which indicate its capability to provide good protection for the cloud environment.

关键词： Webshell detection cloud web security deep learning

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Semi-supervised learning based hybrid beamforming under time-varying propagation environments

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Digital Communications and Networks 2024年第4期10卷 1168-1177页

作者： Yin Long Hang Ding Simon Murphy School of Computer Science and Technology Southwest University of Science and TechnologyMianyang621000China Department of Computing Science University of AlbertaEdmontonT6G 2R3Canada

Hybrid precoding is considered as a promising low-cost technique for millimeter wave(mm-wave)massive Multi-Input Multi-Output(MIMO)*** this work,referring to the time-varying propagation circumstances,with semi-supervised Incremental Learning(IL),we propose an online hybrid beamforming ***,given the constraint of constant modulus on analog beamformer and combiner,we propose a new broadnetwork-based structure for the design model of hybrid *** with the existing network structure,the proposed network structure can achieve better transmission performance and lower ***,to enhance the efficiency of IL further,by combining the semi-supervised graph with IL,we propose a hybrid beamforming scheme based on chunk-by-chunk semi-supervised learning,where only few transmissions are required to calculate the label and all other unlabelled transmissions would also be put into a training data *** the existing single-by-single approach where transmissions during the model update are not taken into the consideration of model update,all transmissions,even the ones during the model update,would make contributions to model update in the proposed *** the model update,the amount of unlabelled transmissions is very large and they also carry some information,the prediction performance can be enhanced to some extent by these unlabelled channel *** results demonstrate the spectral efficiency of the proposed method outperforms that of the existing single-by-single ***,we prove the general complexity of the proposed method is lower than that of the existing approach and give the condition under which its absolute complexity outperforms that of the existing approach.

关键词： Hybrid beamforming Time-varying environments Broad network Semi-supervised learning Online learning

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A comprehensive survey of federated transfer learning:challenges,methods and applications

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Frontiers of computer science 2024年第6期18卷 27-60页

作者： Wei GUO Fuzhen ZHUANG Xiao ZHANG Yiqi TONG Jin DONG Institute of Artificial Intelligence Beihang UniversityBeijing 100191China SKLSDE School of Computer ScienceBeihang UniversityBeijing 100191China School of Computer Science and Technology Shandong UniversityShandong 266237China Beijing Academy of Blockchain and Edge Computing Beijing 100080China

Federated learning(FL)is a novel distributed machine learning paradigm that enables participants to collaboratively train a centralized model with privacy preservation by eliminating the requirement of data *** practice,FL often involves multiple participants and requires the third party to aggregate global information to guide the update of the target ***,many FL methods do not work well due to the training and test data of each participant may not be sampled from the same feature space and the same underlying ***,the differences in their local devices(system heterogeneity),the continuous influx of online data(incremental data),and labeled data scarcity may further influence the performance of these *** solve this problem,federated transfer learning(FTL),which integrates transfer learning(TL)into FL,has attracted the attention of numerous ***,since FL enables a continuous share of knowledge among participants with each communication round while not allowing local data to be accessed by other participants,FTL faces many unique challenges that are not present in *** this survey,we focus on categorizing and reviewing the current progress on federated transfer learning,and outlining corresponding solutions and ***,the common setting of FTL scenarios,available datasets,and significant related research are summarized in this survey.

关键词： federated transfer learning federated learning transfer learning survey

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