Open AccessA Survey on Intrusion Detection Systems Using Various Data Mining Techniques in Big Data Environments
Author(s) -
Sandeep S Budhya
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40128
Subject(s) - big data , intrusion detection system , computer science , computer security , intrusion , analytics , data science , data analysis , order (exchange) , data mining , business , geochemistry , finance , geology
Intrusion Detection is a topic that is of interest both in the corporate world as well as academia. In the advent of Big Data Analytics, multiple analytics techniques can be used on the enormous amounts of data that is being generated every single day in order to discover knowledge. This inherently poses a threat to the security and privacy of all the parties involved. Therefore, it is a necessity in today’s world to reinforce the security systems with robust Intrusion Detection and Prevention Systems. A nominal Cybersecurity System can no longer suffice for detecting and minimizing the damage from cyber-attacks especially since many of the attacks do not fall under a pre-discovered category. In this paper we review the various works particularly concerning Big Heterogeneous Data as well as present opportunities for further research to be conducted in these areas. Keywords: Intrusion, Detection, Cybersecurity, Big Data, Machine Learning, KDDCup99