Big Data Cyber Security Using Machine Learning

ISBN-13: 9786206783206 / Angielski / Miękka / 64 str.

Kandru Arun Kumar; Anuradha Chinta; Kunchala Little Flower

Opis

Cyber security in the context of big data is known to be a critical problem and presents a great challenge to the research community. Machine learning algorithms have been suggested as candidates for handling big data security problems. Among these algorithms, support vector machines (SVMs) have achieved remarkable success on various classification problems. However, to establish an effective SVM, the user needs to deny the proper SVM configuration in advance, which is a challenging task that requires expert knowledge and a large amount of manual effort for trial and error. Here we formulate the SVM configuration process as a bi-objective optimization problem in which accuracy and model complexity are considered as two conflicting objectives. We propose a novel hyper-heuristic framework for bi-objective optimization that is independent of the problem domain. This is the first time that a hyper-heuristic has been developed for this problem. The proposed hyper-heuristic framework consists of a high-level strategy and low-level heuristics.

O autorze

Dr Arun Kumar Kandru Assoc. Professor CSE at Malla Reddy Engineering College, having 13 years of teaching experience.Dr Anuradha Chinta Asst. Professor CSE at V R Siddhartha Engineering College, having 11 years of teaching experience.Dr Kunchala Little Flower Asst. Professor AIML at Malla Reddy University, having 11 years of teaching experience.