Investigation Framework for Cloud Forensics using Dynamic Genetic-based Clustering

Abstract

Cloud computing allows a pool of resources, such as storage, computation power, communication bandwidth, to be shared and accessed by many users from different locations. High dependency on sharing resources among different cloud users allows some attacker to hide and commit crimes using cloud resources and as a result, cloud computing forensics become essential. Many solutions and frameworks for cloud computing forensics have been developed to deal with could based crimes. However, many problems and issues face the proposed solutions and frameworks. In this paper, a new framework for cloud computing forensics is proposed to enhance the investigation process performance and accuracy by adding a new stage to conventional stages. This new stage includes the implementation of a new way for matching based on the LSH algorithm. The proposed framework evaluation results show an improvement for matching and accurate cluster retrieval through the collection process.