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TSWA: a unique approach to overcome interest flooding attacks in the cloud using a combination of TSW and attack detection

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Abstract

The prevalence of distributed denial of service (DDoS) attacks poses a significant challenge to the Internet and cloud environments, including emerging architectures like Named Data Networking (NDN). Among the threats faced by NDN, interest flooding attacks (IFAs) have emerged as a prominent issue. This study presents a novel method for detecting IFAs in NDN by analyzing data name prefix distribution in network traffic to determine the appropriate detection window size. IFAs involve adding a random suffix to a prefix in network traffic, leading to a barrage of interest packets that overwhelm the target without receiving responses. Building upon this observation, a new type of DoS attack called Collaborative Interest Flooding Attack (CIFA) has been identified, which evades existing detection and protection systems using a low-rate attack mode facilitated by collusive manufacturers. To address these challenges, a detection approach combining a rolling time window algorithm and attack detection methodology is proposed. This method evaluates the impact of CIFA attacks on network traffic and examines relevant properties of Pending Interest Table (PIT) entries. Furthermore, the analysis extends to the examination of prefixes in interest packets, providing comprehensive detection of interest flooding attacks. Additionally, the proposed approach effectively restricts the attacker’s port by leveraging the PIT routing character entry to discourage IFA attacks. Experimental results obtained from real-world and simulated scenarios demonstrate the efficacy of the proposed algorithms in detecting DoS attacks. Comparative analysis with existing state-of-the-art methodologies reveals that the proposed approach outperforms them in terms of accuracy, precision, F-Score, GMean, specificity, and sensitivity. By enhancing the detection and mitigation capabilities against interest flooding attacks, this research contributes to the ongoing efforts in securing NDN and future Internet architectures, enabling a more robust and resilient network infrastructure.

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Authors and Affiliations

  1. Lincoln University College, Kota Bharu, Malaysia

    Shaik Khaja Mohiddin

  2. Computer Science and Multimedia, Lincoln University College, Kota Bharu, Selangor, Malaysia

    Divya Midhunchakkaravarthy

  3. R & D Koneru Lakshmaiah Educational Foundation (Deemed to be University), Guntur District, Vaddeswaram, Andhra Pradesh, 522302, India

    Mohammed Ali Hussain

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  3. Mohammed Ali Hussain
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Mohiddin, S.K., Midhunchakkaravarthy, D. & Hussain, M.A. TSWA: a unique approach to overcome interest flooding attacks in the cloud using a combination of TSW and attack detection. Multimed Tools Appl 83, 32673–32713 (2024). https://doi.org/10.1007/s11042-023-16660-8

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