An optimization model of computer network security based on GABP neural network algorithm by Jiangang Wang, Xiaoyan Wang

“…Abstract Background Digital connectivity drives global innovation, ensuring computer network security is more critical than ever. …”
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Network traffic anomaly detection model based on feature grouping and multi‐autoencoders integration by Yang Zhou, Haoyang Zeng, Zhourong Zheng, Wei Zhang

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Dual Feature-Based Intrusion Detection System for IoT Network Security by A. Biju, S. Wilfred Franklin

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Enhancing Security in Industrial IoT Networks: Machine Learning Solutions for Feature Selection and Reduction by Ahmad Houkan, Ashwin Kumar Sahoo, Sarada Prasad Gochhayat, Prabodh Kumar Sahoo, Haipeng Liu, Syed Ghufran Khalid, Prince Jain

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Analysis of features of implementing a “Port scanning” attack using a “Zombie” computer by N. V. Boldyrikhin, M. V. Karpenko, I. A. Sosnovsky, E. A. Yadrets

“…The method is based on computer simulation of a “port scanning” attack using a virtual infrastructure of the network.Result. …”
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Towards edge-collaborative,lightweight and secure region proposal network by Jinbo XIONG, Renwan BI, Qianxin CHEN, Ximeng LIU

“…Aiming at the problem of image privacy leakage and computing efficiency in edge environment,a lightweight and secure region proposal network (SecRPN) was proposed.A series of secure computing protocols were designed based on the additive secret sharing scheme.Two non-collusive edge servers cooperate to perform calculation modules such as secure feature processing,secure anchor transformation,secure bounding-box correction,and secure non-maximum suppression.Theoretical analysis guarantees the correctness and security of SecRPN.The actual performance evaluation shows that SecRPN is outstanding in the computational cost and communication overhead compared with the existing works.…”
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Securable networked scheme with face authentication by Da‐You Huang, Chun‐Liang Lin, Yang‐Yi Chen

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A Lightweight Intrusion Detection System with Dynamic Feature Fusion Federated Learning for Vehicular Network Security by Junjun Li, Yanyan Ma, Jiahui Bai, Congming Chen, Tingting Xu, Chi Ding

“…The rapid integration of complex sensors and electronic control units (ECUs) in autonomous vehicles significantly increases cybersecurity risks in vehicular networks. Although the Controller Area Network (CAN) is efficient, it lacks inherent security mechanisms and is vulnerable to various network attacks. …”
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Intelligent intrusion detection system based on crowd search optimization for attack classification in network security by Chetan Gupta, Amit Kumar, Neelesh Kumar Jain

“…We have developed the hybrid model based on crow search optimization (CSO) and random forest (RF) algorithm for identifying threats and irregularities in a computer network. In comparison to the various state-of-the-art classifiers, the CSO method was applied to the NSL-KDD dataset and the ROSPaCe dataset for the detection of the attacks. …”
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Anomaly Detection Approach Based on Deep Neural Network and Dropout by Zaid Hussien et al.

“…Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. …”
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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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DualAD: Dual adversarial network for image anomaly detection⋆ by Yonghao Wan, Aimin Feng

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LDoS attack detection method based on traffic classification prediction by Liang Liu, Yue Yin, Zhijun Wu, Qingbo Pan, Meng Yue

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Intrusion Detection-Data Security Protection Scheme Based on Particle Swarm-BP Network Algorithm in Cloud Computing Environment by Zhun Wang, Xue Chen

“…Aiming at the problems of low detection rate and high false detection rate of intrusion detection algorithms in the traditional cloud computing environment, an intrusion detection-data security protection scheme based on particle swarm-BP network algorithm in a cloud computing environment is proposed. …”
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Network Security Situational Awareness Based on Improved Particle Swarm Algorithm and Bidirectional Long Short-Term Memory Modeling by Peng Zheng, Yun Cheng, Wei Zhu, Bo Liu, Shuhong Liu, Shijie Wang, Jinyin Bai

“…This indicates a high level of recognition and precision exhibited by the proposed model in detecting network security risk behaviors. Furthermore, in contrast to the traditional CNN neural network, the proposed model is more compact, which significantly reduces the computational overhead and allows for efficient network security situational awareness.…”
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Adversarial Threats to Cloud IDS: Robust Defense With Adversarial Training and Feature Selection by Hariprasad Holla, Shashidhar Reddy Polepalli, Arun Ambika Sasikumar

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HealthChain: A blockchain‐based framework for secure and interoperable electronic health records (EHRs) by Ghassan Husnain, Zia Ullah, Muhammad Ismail Mohmand, Mansoor Qadir, Khalid J. Alzahrani, Yazeed Yasin Ghadi, Hend Khalid Alkahtani

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Adversarial Robustness of Self-Supervised Learning Features by Nicholas Mehlman, Shri Narayanan

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

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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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