Using network data to improve digital investigation in cloud computing environments

With the rise of cloud computing environments and the increasingly ubiquitous utilization of its opportunities, the amount of data analysed in a traditional digital forensic examination is increasing significantly, thus increasing the risk to miss evidence. Without adopting new methodology or different approaches investigators are unable to guarantee a valid digital forensic investigation. Due to the large amount of cloud platforms it is hardly feasible to identify them when investigating a computer. Knowing all different services of cloud computing platforms is impossible for a human. The paper therefore proposes to investigate raw network data in order to improve the complete digital investigation process by correlating network and computer forensic parts. We present a new method to analyse network traffic to find information about the usage of cloud specific data. With the possibility to automate this extraction and the comparison with a cloud service knowledge base, the error rate of a forensic investigation is reduced. It also reduces the risk of human errors.