Ensemble-based multi-filter feature selection method for DDoS detection in cloud computing

By Opeyemi A. Osanaiye, Haibin Cai, Kim-Kwang Raymond Choo, Ali Dehghantanha, Zheng Xu, Mqhele E. Dlodlo. EURASIP Journal on Wireless Communications and Networking, 2016

328 citations recorded by the source corpus.

Widespread adoption of cloud computing has increased the attractiveness of such services to cybercriminals. Distributed denial of service (DDoS) attacks targeting the cloud’s bandwidth, services and resources to render the cloud unavailable to both cloud providers, and users are a common form of attacks. In recent times, feature selection has been identified as a pre-processing phase in cloud DDoS attack defence which can potentially increase classification accuracy and reduce computational complexity by identifying important features from the original dataset during supervised learning. In this work, we propose an ensemble-based multi-filter feature selection method that combines the output of four filter methods to achieve an optimum selection. We then perform an extensive experimental evaluation of our proposed method using intrusion detection benchmark dataset, NSL-KDD and decision tree classifier. The findings show that our proposed method can effectively reduce the number of features from 41 to 13 and has a high detection rate and classification accuracy when compared to other classification techniques.

Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/99540ca0c3d49c4041d3fc2ab80edb4ffc3ece9b

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Citations in the corpus

Text feature extraction based on deep learning: a review (2017, methodology): “In reference [26], this paper presented an ensemble-based multi-filter feature selection method that combines the output of one third split of ranked important features of information gain, gain ratio, chi-squared, and ReliefF.”
A systematic literature review of blockchain cyber security (2020, unknown): “It also has been a signi ﬁ cant factor affecting the proliferation of ﬁ nancially driven cyber-attacks [14], such as ransomware [15] and denial of service [16] against retailers and other online organizations.”
From Cloud to Fog Computing: A Review and a Conceptual Live VM Migration Framework (2017, background): “For example, DDoS attacks while not new [100], [121] are one hard-to-mitigate attacks in fog and cloud computing.”