Secure Virtual Desktop Infrastructure Solution Using Homomorphic Encryption and Machine Learning Models
W.M.D Senuwan, Nimantha Dissanayake, Malithi Disanayaka, Shashini Hewage, Kavinga Yapa Abeywardena, Deemantha Siriwardhana · 2024
In the recent past, Virtual Desktop Infrastructure (VDI) technology has experienced rapid growth. Although many enterprise companies have implemented VDI systems, previous research has highlighted several critical issues, including data breaches and session hijacking. Security measures identified for such threats were suboptimal, especially for the firms with fewer resources. In this paper, authors combat existing threats to VDI systems with different technologies such as Homomorphic Encryption (HE) for the safe exchange of location data, and the Machine Learning (ML) model is used for real-time log analysis, thereby making it easy to detect some level of anomaly in the complex VDI environments. According to the result, this integrated posture introduces a new and positive dimension in VDI strengthening the security and privacy of data, while protecting against various threats. Additionally, the paper also addresses setting a new and more secure base for any virtualization technologies all while securely handling consumer data.