One-Class ELM Ensemble-Based DDoS Attack Detection in Multimedia Cloud Computing

View Sample PDF

Author(s): Gopal Singh Kushwah (National Institute of Technology, Kurukshetra, India), Surjit Singh (Thapar Institute of Engineering and Technology, India)and Sumit Kumar Mahana (National Institute of Technology, Kurukshetra, India)
Copyright: 2023
Pages: 18
Source title: Examining Multimedia Forensics and Content Integrity
Source Author(s)/Editor(s): Sumit Kumar Mahana (National Institute of Technology, Kurukshetra, India), Rajesh Kumar Aggarwal (National Institute of Technology, Kurukshetra, India)and Surjit Singh (Thapar Institute of Engineering and Technology, India)
DOI: 10.4018/978-1-6684-6864-7.ch002

Keywords: Forensics & Investigations / Information Science Reference / Multimedia Technology / Security & Forensics

Purchase

View One-Class ELM Ensemble-Based DDoS Attack Detection in Multimedia Cloud Computing on the publisher's website for pricing and purchasing information.

Abstract

Distributed denial of service (DDoS) attack affects the availability of multimedia cloud services to its users. In this attack, a huge traffic load is put on the victim server. Hence initially the server becomes slow to process legitimate requests and later becomes unavailable. Therefore implementing defensive solutions against these attacks is of utmost importance. In this work, the authors propose a bagging ensemble-based DDoS attack detection system for multimedia cloud computing. One class extreme learning machine (ELM) is used as a base classifier. An outlier detection based approach has been used to detect these attacks. Experiments have been performed using two benchmark datasets NSL-KDD and CICIDS2017 to evaluate the performance of the proposed system.

The IRMA Community

Research IRM

One-Class ELM Ensemble-Based DDoS Attack Detection in Multimedia Cloud Computing

Purchase

Abstract

Related Content

IRMA Sponsors