Case Study

Machine learning has played a crucial role lately in the progress made in the field of technology, thereby providing a wide range of applications. This chapter reflects the developments made in pattern recognition and machine learning technologies targeting at its applications in the field of mobile networks. Since mobile networks specifically MANETs are prone to numerous kinds of intrusions and attacks, designing a defense system oriented on the notion of pattern recognition is hardly concentrated by the researches. Pattern recognition is widely used to study the patterns in the data through the applications and implementation of extensive algorithms which are either classification based or clustering based. With the aim to provide a better understanding of how the pattern recognition can be applicable as an IDS to an unrelated area like networks, a case study is done for detecting anomalies by deploying the black hole attack in the network using QualNet simulator. The prime idea of this chapter is to comprehend the practical applications of machine learning accompanied with pattern recognition through the medium of MATLAB software to formulate an IDS countering the black hole attack.