Abstract
Machine learning is a set of skills to understand the nature of data and its characteristics. Machine learning has been a primary approach to the unknown data world, which is an emerging topic in the Information Systems domain for decades. Our research pinned the importance of machine learning in the cyber security area, in particular, the intrusion detection context. One of the primary aspects of intrusion detection is to forecast unexpected future events or compromising activities from the third party. If machine learning aids such as anticipating behaviors in advance, the loss of informational assets and incurring costs will be minimized. The current study reviewed machine learning and its applicability and suggests some strategies in the cybersecurity domain. Discussions and limitations are followed.
Recommended Citation
Kairu, Mumbi and Shin, Soo Il, "EVALUATING THE USE OF MACHINE LEARNING FOR CYBER SECURITY INTRUSION DETECTION" (2022). SAIS 2022 Proceedings. 27.
https://aisel.aisnet.org/sais2022/27