Bit-and-Piece DDoS attack Detection based on the Statistical Metrics
T. Subburaj1, K. Suthendran2
1T. Subburaj, Department of Computer Applications, Kalasalingam Academy of Research and Education, Krishnankoil (Tamil Nadu), India.
2K. Suthendran, Department of Information Technology, Kalasalingam Academy of Research and Education, Krishnankoil (Tamil Nadu), India.
Manuscript received on 23 November 2019 | Revised Manuscript received on 17 December 2019 | Manuscript Published on 30 December 2019 | PP: 48-55 | Volume-9 Issue-1S4 December 2019 | Retrieval Number: A10861291S419/19©BEIESP | DOI: 10.35940/ijeat.A1086.1291S419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: On each successive day, the DDoS attacks are increasing, improving and becoming more critical than ever before. In 2018, CISCO predicted that DDoS attack traffics may reach to 3.1 billion during 2021. Bit and Piece DDoS attack is an emerging attacking technique was found and reported by Nexusguard. This attack mainly targets the communication service providers and it injects unwanted junk information in to the legitimate traffic and thus bypasses the detection techniques. This work is aimed to propose a novel approach for detecting bit and piece attack using statistical metrics. Here, the packet flow is monitored at every second and the variations in the data flows easily identified as an attack.
Keywords: DDoS Attack, Entropy, Bit and Piece, Security.
Scope of the Article: Security, Privacy and Trust in IoT & IoE