Ensemble Learning Mechanisms for Threat Detection

Author:

Arul Rajakumar1,Moorthy Rajalakshmi Shenbaga2,Bashir Ali Kashif3

Affiliation:

1. Amrita Vishwa Vidyapeetham, India

2. St. Joseph's Institute of Technology, India

3. Manchester Metropolitan University, UK

Abstract

Technology evolution in the network security space has been through many dramatic changes recently. Enhancements in the field of telecommunication systems invite fruitful security solutions to address various threats that arise due to the exponential growth in the number of users. It's crucial for upgrading the entire infrastructure to safeguard the system from specific threats. So, there is a huge demand for the learning mechanism to realize the behavior of attacks. Recent upcoming technologies like machine learning and deep learning can support in the process of learning the behavior of all types of attacks irrespective of their deployment criteria. In this chapter, the analysis of various machine learning algorithms with respect to a few scenarios that can be adopted for the benefits of improving the security standard of the network. This chapter briefly discusses various know attacks and their classification and how machine learning algorithms can be involved to overcome the popular attacks. Also, various intrusion detection and prevention schemes were discussed in detail.

Publisher

IGI Global

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