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  • Open Access

    ARTICLE

    Intrusion Detection Using Federated Learning for Computing

    R. S. Aashmi1,*, T. Jaya2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1295-1308, 2023, DOI:10.32604/csse.2023.027216

    Abstract The integration of clusters, grids, clouds, edges and other computing platforms result in contemporary technology of jungle computing. This novel technique has the aptitude to tackle high performance computation systems and it manages the usage of all computing platforms at a time. Federated learning is a collaborative machine learning approach without centralized training data. The proposed system effectively detects the intrusion attack without human intervention and subsequently detects anomalous deviations in device communication behavior, potentially caused by malicious adversaries and it can emerge with new and unknown attacks. The main objective is to learn overall behavior of an intruder while… More >

  • Open Access

    ARTICLE

    Abnormal Event Correlation and Detection Based on Network Big Data Analysis

    Zhichao Hu1, Xiangzhan Yu1,*, Jiantao Shi1, Lin Ye1,2

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 695-711, 2021, DOI:10.32604/cmc.2021.017574

    Abstract With the continuous development of network technology, various large-scale cyber-attacks continue to emerge. These attacks pose a severe threat to the security of systems, networks, and data. Therefore, how to mine attack patterns from massive data and detect attacks are urgent problems. In this paper, an approach for attack mining and detection is proposed that performs tasks of alarm correlation, false-positive elimination, attack mining, and attack prediction. Based on the idea of CluStream, the proposed approach implements a flow clustering method and a two-step algorithm that guarantees efficient streaming and clustering. The context of an alarm in the attack chain… More >

  • Open Access

    ARTICLE

    Benchmarking Approach to Compare Web Applications Static Analysis Tools Detecting OWASP Top Ten Security Vulnerabilities

    Juan R. Bermejo Higuera1, *, Javier Bermejo Higuera1, Juan A. Sicilia Montalvo1, Javier Cubo Villalba1, Juan José Nombela Pérez1

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1555-1577, 2020, DOI:10.32604/cmc.2020.010885

    Abstract To detect security vulnerabilities in a web application, the security analyst must choose the best performance Security Analysis Static Tool (SAST) in terms of discovering the greatest number of security vulnerabilities as possible. To compare static analysis tools for web applications, an adapted benchmark to the vulnerability categories included in the known standard Open Web Application Security Project (OWASP) Top Ten project is required. The information of the security effectiveness of a commercial static analysis tool is not usually a publicly accessible research and the state of the art on static security tool analyzers shows that the different design and… More >

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