2017Unpublished venueRequires access

A Lightweight Approach to Detect the Low/High Rate IP Spoofed Cloud DDoS Attacks

Neha Agrawal, Shashikala Tapaswi

Open publisher page 21 citations

Abstract

In cloud computing, broadly two facets of Distributed Denial-of-Service (DDoS) attack exist. The attacker uses Internet Protocol (IP) spoofing technique for launching the DDoS attack to disguise the source's identity. Consequently, its detection becomes a crucial and challenging task. The objective of the paper is to propose an adaptive and lightweight approach which can detect the low and high rate spoofed DDoS attack traffic accurately. The approach is implemented in a closed cloud environment. The experimental results showed that the approach can effectively detect internal and external low/high rate spoofed DDoS attacks with 99.3% accuracy and provides better performance.

About this research paper

What this paper is about

In cloud computing, broadly two facets of Distributed Denial-of-Service (DDoS) attack exist. The attacker uses Internet Protocol (IP) spoofing technique for launching the DDoS attack to disguise the source's identity. Consequently, its detection becomes a crucial and challenging task. The objective of the paper is to propose an adaptive and lightweight approach which can detect the low and high rate spoofed DDoS attack traffic accurately. The approach is implemented in a closed cloud environment. The experimental results showed that the approach can effectively detect internal and external low/high rate spoofed DDoS attacks with 99.3% accuracy and provides better performance.

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OpenAlex reports 21 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In cloud computing, broadly two facets of Distributed Denial-of-Service (DDoS) attack exist. The attacker uses Internet Protocol (IP) spoofing technique for launching the DDoS attack to disguise the source's identity. Consequently, its detection becomes a crucial and challenging task. The objective of the paper is to propose an adaptive and lightweight approach which can detect the low and high rate spoofed DDoS attack traffic accurately. The approach is implemented in a closed cloud environment. The experimental results showed that the approach can effectively detect internal and external low/high rate spoofed DDoS attacks with 99.3% accuracy and provides better performance.

Key concepts: Spoofing attack, Denial-of-service attack, Computer science, IP address spoofing, Application layer DDoS attack, Trinoo, Cloud computing, Computer security

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