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  • Open Access

    ARTICLE

    A Model Training Method for DDoS Detection Using CTGAN under 5GC Traffic

    Yea-Sul Kim1, Ye-Eun Kim1, Hwankuk Kim2,*

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1125-1147, 2023, DOI:10.32604/csse.2023.039550 - 26 May 2023

    Abstract With the commercialization of 5th-generation mobile communications (5G) networks, a large-scale internet of things (IoT) environment is being built. Security is becoming increasingly crucial in 5G network environments due to the growing risk of various distributed denial of service (DDoS) attacks across vast IoT devices. Recently, research on automated intrusion detection using machine learning (ML) for 5G environments has been actively conducted. However, 5G traffic has insufficient data due to privacy protection problems and imbalance problems with significantly fewer attack data. If this data is used to train an ML model, it will likely suffer… More >

  • Open Access

    ARTICLE

    Rule-Based Anomaly Detection Model with Stateful Correlation Enhancing Mobile Network Security

    Rafia Afzal, Raja Kumar Murugesan*

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1825-1841, 2022, DOI:10.32604/iasc.2022.020598 - 09 October 2021

    Abstract The global Signalling System No. 7 (SS7) network protocol standard has been developed and regulated based only on trusted partner networks. The SS7 network protocol by design neither secures the communication channel nor verifies the entire network peers. The SS7 network protocol used in telecommunications has deficiencies that include verification of actual subscribers, precise location, subscriber’s belonging to a network, absence of illegitimate message filtering mechanism, and configuration deficiencies in home routing networks. Attackers can take advantage of these deficiencies and exploit them to impose threats such as subscriber or network data disclosure, intercept mobile… More >

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