Enhancing Cloud Service Performance by Mitigating DDoS‎Attacks with Multilevel Time-Oriented Analysis

  • Authors

    • Dhiyanesh B Assistant professor/CSE, SRM Institute of Science and Technology, Vadapalani campus, Chennai, Tamil Nadu, India
    • Dayana R Assistant professor/CSE, SRM Institute of Science and Technology, Vadapalani campus, Chennai, Tamil Nadu, India
    • Saranya N Assistant Professor/AIDS, Karpagam College of Engineering, Coimbatore, Tamil Nadu, India
    • Daniel Madan Raja S Associate Professor, CSE, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India
    • Jayashree V Assistant Professor/IT, K. Ramakrishnan College of Engineering, Trichy, Tamil Nadu, India
    https://doi.org/10.14419/0g6p7166

    Received date: July 15, 2025

    Accepted date: July 24, 2025

    Published date: November 1, 2025

  • Multilevel Time-Oriented Analysis; Service Performance; Trust Verification; Service History Monitoring; DDoS Detection; Malicious ‎Requests

  • Abstract

    In many organizations, cloud computing is becoming increasingly common. Distributed Denial of Service (DDoS) attacks are a concern that can ‎be mitigated in several ways, but they have a noticeable impact on service performance. Most methods perform trust verification only at the initial ‎stage, but malicious activities often occur at the middle or end stage. It highly affects the service performance of the user, and it should be ‎monitored and stopped initially. A Multilevel Time Oriented Analysis (MLTOA) is performed to identify such malicious requests. The ‎high-threat service is determined by tracking the service history in different states. Using the MLTOA scheme, the service history can be ‎grouped into other states, and the user service break that occurs in any state can be identified. Then the method backtracks two states: one is the ‎initial state of the request, and the second is how the malicious user starts the service request. Thus, detecting DDoS attacks can be performed ‎efficiently by monitoring such states and deciding whether they are malicious or genuine. Therefore, the method does not allow the user to access ‎the service. DDoS detection accuracy increases dramatically with the proposed method, reduced time complexity, and improved service ‎utilization‎.

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  • How to Cite

    B, D. ., R, D. ., N, S., S, D. M. R. ., & V, J. . (2025). Enhancing Cloud Service Performance by Mitigating DDoS‎Attacks with Multilevel Time-Oriented Analysis. International Journal of Basic and Applied Sciences, 14(SI-1), 585-593. https://doi.org/10.14419/0g6p7166