• Mr.Raj Kumar T
• Mrs. R Reshma Ramesh
• Dr. Sobhana N V

Cloud computing bought about an incredible overhaul of the phenomenon of companies having to put in significant capital investments to build software and IT infrastructure. It assurances to help organizations save money on IT expenditure while increasing reliability, efficiency, and productivity. However, despite the potential benefits that the cloud promises its users, it is facing some security issues like data loss, insider threat, outsider threat, data breaches, malware injection, etc. Still, insider threats persist as one of the major concerns because insider threat is a security risk to an organization that comes from within the business itself. Although the number of insider threats is much lower than external network attacks, insider threats can cause widespread damage. As insiders are very aware of an organization’s system, it is very difficult to detect their malicious behavior. In this paper, we propose the need of insider-threat detection methods based on user behavior modeling and anomaly detection algorithms such as Binary classification and Logistics Regression algorithm to detect malicious activities.

cloud computing, security issues, insider threat, behavioral modeling

"IDENTIFICATION OF INSIDER THREAT IN A CLOUD-BASED SYSTEM- A REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 5, page no.f189-f194, May-2021, Available :http://www.jetir.org/papers/JETIR2105691.pdf

"IDENTIFICATION OF INSIDER THREAT IN A CLOUD-BASED SYSTEM- A REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 5, page no. ppf189-f194, May-2021, Available at : http://www.jetir.org/papers/JETIR2105691.pdf