Survey on data security and privacy-preserving for the research of edge computing by Jiale ZHANG, Yanchao ZHAO, Bing CHEN, Feng HU, Kun ZHU

“…With the rapid development and extensive application of the Internet of things (IoT),big data and 5G network architecture,the massive data generated by the edge equipment of the network and the real-time service requirements are far beyond the capacity if the traditional cloud computing.To solve such dilemma,the edge computing which deploys the cloud services in the edge network has envisioned to be the dominant cloud service paradigm in the era of IoT.Meanwhile,the unique features of edge computing,such as content perception,real-time computing,parallel processing and etc.…”
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DualAD: Dual adversarial network for image anomaly detection⋆ by Yonghao Wan, Aimin Feng

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Resource-Efficient Traffic Classification Using Feature Selection for Message Queuing Telemetry Transport-Internet of Things Network-Based Security Attacks by Emmanuel Tuyishime, Marco Martalò, Petru A. Cotfas, Vlad Popescu, Daniel T. Cotfas, Alexandre Rekeraho

“…Anomaly detection, primarily through traffic classification supported by artificial intelligence and machine learning techniques, has emerged as a practical approach to enhancing IoT network security. Effective traffic classification requires efficient feature selection, which is critical for resource-constrained IoT devices with limited computational power, memory, and energy. …”
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Machine learning based multi-stage intrusion detection system and feature selection ensemble security in cloud assisted vehicular ad hoc networks by C. Christy, A. Nirmala, A. Mary Odilya Teena, A. Isabella Amali

“…This research ensures next-generation transport networks’ secure and reliable functioning and prepares the path for VANET protection upgrades. …”
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Metaheuristic Algorithms for Optimization and Feature Selection in Cloud Data Classification Using Convolutional Neural Network by Nandita Goyal, Munesh Chandra Trivedi

“…Cloud forensics plays a vital role to address the security issues related to cloud computing by identifying, collecting and studying digital evidence in cloud environment.The aim of the research paper is to explore the concept of cloud forensic by applying optimization for feature selection before classification of data on cloud side. …”
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ENHANCING NETWORK INTRUSION DETECTION USING MACHINE LEARNING AND META-MODELLING FOR IMPROVED CYBER SECURITY PERFORMANCE by Sunita, Pankaj Verma, Nitika, Jaspreet Kaur, Vijay Rana

“…This study is based on the analysis of network intrusion detection and the improvement of various machine learning methods that produce high accuracy and guarantee secure network traffic from malicious activities. …”
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Network intrusion detection model using wrapper based feature selection and multi head attention transformers by Muhammad Umer, Muhammad Tahir, Muhammad Sardaraz, Muhammad Sharif, Hela Elmannai, Abeer D. Algarni

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YOLO-LSD: A Lightweight Object Detection Model for Small Targets at Long Distances to Secure Pedestrian Safety by Ming-An Chung, Sung-Yun Chai, Ming-Chun Hsieh, Chia-Wei Lin, Kai-Xiang Chen, Shang-Jui Huang, Jun-Hao Zhang

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Minimising Security Deviations in Software-Defined Networks Using Deep Learning by mohammed alghaloom

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Systematic Approach for Malware Detection in IoT Devices: Enhancing Security and Performance by Vasudeva Pai, B. H. Karthik Pai, G. S. Sudhiksha, Vandya Kamath, K. Varsha, S. Manjunatha

“…These include ensemble methods such as Bagging, Stacking, Voting, AdaBoost, and H2O AutoML, as well as advanced models such as sparse neural networks with pruning and feature selection and regularized classifiers L1. …”
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Hybrid Convolutional Neural Network-Based Intrusion Detection System for Secure IoT Networks by Sami Qawasmeh, Ahmad Habboush, Bassam Elzaghmouri, Qasem Kharma, Da'ad Albalawneh

“…CNN-based intrusion detection in IoT networks is stressed in the study. It shows how hybrid CNN-based techniques can improve IoT network security and resilience. …”
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Research on performance optimizations for TCM-KNN network anomaly detection algorithm by LI Yang1, GUO Li1, LU Tian-bo3, TIAN Zhi-hong1

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TriageHD: A Hyper-Dimensional Learning-to-Rank Framework for Dynamic Micro-Segmentation in Zero-Trust Network Security by Ryozo Masukawa, Sanggeon Yun, Sungheon Jeong, Nathaniel D. Bastian, Mohsen Imani

“…This paper presents TriageHD, a novel framework that integrates graph-based Hyper-Dimensional Computing (HDC) with a learning-to-rank algorithm to strengthen zero-trust network security. …”
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Study and Developing a Network Security Prototype Based on Agent Technology by Najla Ibraheem, Haleema Sulaiman

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Effects of feature selection and normalization on network intrusion detection by Mubarak Albarka Umar, Zhanfang Chen, Khaled Shuaib, Yan Liu

“…However, the advent of larger IDS datasets has negatively impacted the performance and computational complexity of AI-based IDSs. Many researchers used data preprocessing techniques such as feature selection and normalization to overcome such issues. …”
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Weapon detection with FMR-CNN and YOLOv8 for enhanced crime prevention and security by Shanthi P, Manjula V

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An Efficient and Secure Session Key Management Scheme in Wireless Sensor Network by Gulzar Mehmood, Muhammad Sohail Khan, Abdul Waheed, Mahdi Zareei, Muhammad Fayaz, Tariq Sadad, Nazri Kama, Azri Azmi

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Literature Review on Using Internet Protocol Security (IPsec) on network Connectivity by Twana Saeed Ali

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An Efficient and Hybrid Deep Learning-Driven Model to Enhance Security and Performance of Healthcare Internet of Things by Muhammad Babar, Muhammad Usman Tariq, Basit Qureshi, Zabeeh Ullah, Fahim Arif, Zahid Khan

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Temporal-Spatial Feature Extraction in IoT-Based SCADA System Security: Hybrid CNN-LSTM and Attention-Based Architectures for Malware Classification and Attack Detection by Onur Polat, Ali Ayid Ahmad, Saadin Oyucu, Enes Algul, Ferdi Dogan, Ahmet Aksoz

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