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Predictive machine learning-based integrated approach for DDoS detection and prevention

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Abstract

Distributed Denial of Service attack has been a huge threat to the Internet and may carry extreme losses to systems, companies, and national security. The invader can disseminate Distributed denial of service (DDoS) attacks easily, and it ends up being significantly harder to recognize and forestall DDoS attacks. In recent years, many IT-based companies are attacked by DDoS attacks. In this view, the primary concern of this work is to detect and prevent DDoS attacks. To fulfill the objective, various data mining techniques such that Jrip, J48, and k-NN have been employed for DDoS attacks detection. These algorithms are implemented and thoroughly evaluated individually to validate their performance in this domain. The presented work has been evaluated using the latest dataset CICIDS2017. The dataset characterizes different DDoS attacks viz. brute force SSH, brute force FTP, Heartbleed, infiltration, botnet TCP, UDP, and HTTP with port scan attack. Further, the prevention method takes place in progress to block the malicious nodes participates in any of the said attacks. The proposed DDoS prevention works in a proactive mode to defend all these attack types and gets evaluated concerning various parameters such as Throughput, PDR, End-to-End Delay, and NRL. This study claimed that the proposed technique outperforms with respect to the AODV routing algorithm.

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Public datasets have been used.

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Authors and Affiliations

  1. Department of Information Technology, Hawassa University Institute of Technology, Hawassa, Ethiopia

    Solomon Damena Kebede

  2. Department of Computer Science, Hawassa University Institute of Technology, Hawassa, Ethiopia

    Basant Tiwari

  3. Department of CSE, Dr. S P Mukherjee IIIT-NR, Raipur, India

    Vivek Tiwari

  4. Department of Information Technology, LNCT, Bhopal, India

    Kamlesh Chandravanshi

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  1. Solomon Damena Kebede
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  2. Basant Tiwari
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  3. Vivek Tiwari
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  4. Kamlesh Chandravanshi
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Correspondence to Vivek Tiwari.

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Kebede, S.D., Tiwari, B., Tiwari, V. et al. Predictive machine learning-based integrated approach for DDoS detection and prevention. Multimed Tools Appl 81, 4185–4211 (2022). https://doi.org/10.1007/s11042-021-11740-z

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  • DOI: https://doi.org/10.1007/s11042-021-11740-z

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