The diverse characteristics of cloud computing like the ease of global network access, virtualization makes it a leader in the market. Along with the ease, the attack surface is a major setback in the security. Cloud forensics is one of the measures to provide a solution to security concerns. It helps in analyzing and investigating the attack. It focuses on gathering relevant evidence to support the investigation. In this paper, we focus on performing a comparative analysis of algorithms for data captured in virtualized cloud environment. This research contributes to providing the most efficient analysis algorithm for detecting the anomalies in the cloud data. The cloud data set is created in the simulated environment over KVM, using Wireshark. The concerned algorithms are Decision Tree, Naïve Bayes, SVM, and KNN. With the results, it was analyzed that Decision tree is the most efficient algorithm amongst the concerned ones for analysis over virtualized cloud data.