Global optimization algorithm is developed by inspiring natural phenomena such as foraging behavior, evolution, cell and molecular phenomena, reproduction, cognition and neuro systems, alignment phenomena in microscopes, non-biological systems and geo-science based techniques as source of metaphor for problem solving.
Published in Chapter:
Review on Intelligent Algorithms for Cyber Security
P. Subashini (Avinshilingam Institute for Home Science and Higher Education for Women, India), M. Krishnaveni (Avinashilingam Institute for Home Science and Higher Education for Women, India), T. T. Dhivyaprabha (Avinashilingam Institute for Home Science and Higher Education for Women, India), and R. Shanmugavalli (Avinashilingam Institute for Home Science and Higher Education for Women, India)
Copyright: © 2020
|Pages: 22
DOI: 10.4018/978-1-5225-9611-0.ch001
Abstract
Cyber security comprises of technologies, architecture, infrastructure, and software applications that are designed to protect computational resources against cyber-attacks. Cyber security concentrates on four main areas such as application security, disaster security, information security, and network security. Numerous cyber security algorithms and computational methods are introduced by researchers to protect cyberspace from undesirable invaders and susceptibilities. But, the performance of traditional cyber security algorithms suffers due to different types of offensive actions that target computer infrastructures, architectures and computer networks. The implementation of intelligent algorithms in encountering the wide range of cyber security problems is surveyed, namely, nature-inspired computing (NIC) paradigms, machine learning algorithms, and deep learning algorithms, based on exploratory analyses to identify the advantages of employing in enhancing cyber security techniques.