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

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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

“…Analyze the implementation features of a “Port scanning” attack using a “Zombie” computer to hide the IP address of the attacking machine.Method. …”
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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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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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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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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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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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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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LDoS attack detection method based on traffic classification prediction by Liang Liu, Yue Yin, Zhijun Wu, Qingbo Pan, Meng Yue

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

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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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Research on cloud computing users’ public safety trust model based on scorecard-random forest by Shengli ZHOU, Canghong JIN, Lifa WU, Zheng HONG

“…Traditional cloud computing trust models mainly focused on the calculation of the trust of users’ behavior.In the process of classification and evaluation,there were some problems such as ignorance of content security and lack of trust division verification.Aiming to solve these problems,cloud computing users’ public safety trust model based on scorecard-random forest was proposed.Firstly,the text was processed using Word2Vec in the data preprocessing stage.The convolution neural network (CNN) was used to extract the sentence features for user content tag classification.Then,scorecard method was used to filter the strong correlation index.Meanwhile,in order to establish the users’ public safety trust evaluation model in cloud computing,a random forest method was applied.Experimental results show that the proposed users’ public safety trust evaluation model outperforms the general trust evaluation model.The proposed model can effectively distinguish malicious users from normal users,and it can improve the efficiency of the cloud computing users management.…”
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Securable networked scheme with face authentication by Da‐You Huang, Chun‐Liang Lin, Yang‐Yi Chen

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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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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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Applications of big data cognitive computing in content security governance by Xuetao DU

“…In the communication network, there is a mass of bad information needed to be read and understood to extract useful knowledge and features for governance.Methods based on manual analysis can not achieve this goal.It is necessary to adopt the big-data-based cognitive computing technology to help to understand massive data and customize content security strategies.Aiming at four practical problems including telecommunication fraud governance, bad message governance, variant message governance and bad website governance, the big data cognitive computing solutions were put forward, and the practical results were given.The results show that the solutions could find the bad information quickly, and improve the quality of the content security governance effectively.…”
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DualAD: Dual adversarial network for image anomaly detection⋆ by Yonghao Wan, Aimin Feng

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