Distributed denial of service attacks detection in cloud computing using extreme learning machine. (2nd July 2019)

• Record Type: Journal Article
• Authors: Kushwah, Gopal Singh; Ali, Syed Taqi
• Is Part Of: International journal of communication networks and distributed systems. Volume 23:Number 3(2019)
• Page Start: 328
• Page End: 351
• Publication Date: 2019-07-02
• Subjects: cloud computing -- DDoS attack -- extreme learning machines -- ELM -- artificial neural networks -- ANN -- cloud security -- machine learning; Computer networks -- Periodicals; Telecommunication systems -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; 004.6
• Languages: English
• ISSNs: 1754-3916

Abstract

Cloud computing has become popular due to its on-demand, pay-as-you-use and ubiquitous features. This technology suffers from various security risks. Distributed denial of service (DDoS) attack is one of these security risks. It is used to disrupt the services provided by cloud computing. In DDoS attack, the cloud server is overwhelmed with fake requests by the attacker. This makes long response time for legitimate users or shut down of the service completely. In this work, a DDoS attack detection model based on extreme learning machine (ELM) has been proposed. Experiments show that proposed model can be trained in a very short period of time and provides high detection accuracy.