Digital Forensics Challenges to Big Data in the Cloud

Abstract

As a new research area, Digital Forensics is a subject in a rapidly developing society. Cyber Security for Big Data in the Cloud is getting more attention than ever. A computing breach requires digital forensics to seize digital evidence to determine who is responsible and what has been done maliciously and the possible further consequences. In particular, for Big Data attack cases, Digital Forensics is facing even more challenge for earlier digital breach investigations. For the PPI (Protection of Personal Information) a GDPR (General Data Protection Regulation) law has been launched to be implemented from the 25th May 2018. This compulsory regulation will have an important impact on healthcare PPI in the cloud (ICO, 2017, Deloitte, 2014). Nowadays, Big Data with the characteristics of three “V”s (Volume, Velocity, and Variety), are either synchronized with the Cloud, or stored in the Cloud, in order to solve the storage capacity and so on problems, which made Digital Forensics investigation even more difficult. The Big Data Digital Forensics issue for the Cloud is difficult. One of them is the need to identify which physical devices have been compromised. Data are distributed in the Cloud, so the customer or digital forensics practitioner cannot have full access control like the traditional investigation does. Smart City are making use of ICT (information communications technology) to collect, detect, analyze and integrate the key information data of core systems in running the cities. Meanwhile, the Control Centre is making intelligent responses to different requirements that include daily livelihood, PPI security, environmental protection, public safety, industrial and commercial activities and city services. The Smart City healthcare Big Data are collected and gathered by the IoT (Internet of Things) (Liu, 2014, Qi, 2016) and applying GDPR prevent Cyberstalking and Cybercrimes. This paper summerises our review on the trends of Digital Forensics used for Big Data. The evidence acquisition challenge is discussed. A case study of a Smart City project with IoT services collecting Big Data which are stored in the Cloud computing environment is represented. The techniques can be generalised to other Big Data in the Cloud environment.