When using an iterative method to train a learner, this type of regularisation is employed to avoid overfitting.
Published in Chapter:
Using Deep Learning and Big Data Analytics for Managing Cyber-Attacks
Sarabjeet Kaur Kochhar (Indraprastha College for Women, University of Delhi, Delhi, India), Anishka Bhatia (Indraprastha College for Women, University of Delhi, Delhi, India), and Nandini Tomer (Indraprastha College for Women, University of Delhi, Delhi, India)
Copyright: © 2023
|Pages: 33
DOI: 10.4018/978-1-6684-5722-1.ch008
Abstract
This chapter acquaints the reader to the terms and terminologies of cyber-attacks, cybersecurity, big data, data analytics, and related new age technologies, including deep learning. The types of cyber-attacks, how they become special and different within the big data analytic frameworks, a multi-layer framework for their detection, and the challenges therein are detailed next. Thereafter, an extensive review of some research works has been undertaken to provide an in-depth insight to the various cyber security detection systems using the new age technologies such as naive Bayesian networks in intrusion detection systems, deep learning in Android malware detection, and intelligent malware detection, etc. Conclusions have been drawn from these studies to establish that the emerging technologies, like artificial intelligence, machine learning, deep learning, and internet of Things, are the need of the hour to assist organizations in navigating the increasingly aggressive cyber threat landscape.