Application of Artificial Intelligence in Digital Forensic Readiness Using Intelligence Reports

Many organizations have published yearly reports on cloud security threat intelligence. These reports have shown a drastic increase in security attacks on cloud computing services. Such reports end up gathering dust without exploiting the reports' usefulness due to their sheer size. The threats have to be analysed timeously to provide and anticipate solutions before further security attacks occur. With the increase in cloud computing usage, there has been an increase in security breaches. The cloud also adds to an aspect of volatility in provisioning of services and at the edge components availability. Incidents which have already been captured in incidents reports can be used to conduct digital forensic investigations (DFIs). For DFI process to be conducted, there is need for the environment to be prepared beforehand, thus, to say, the environment such as the cloud, should be digital forensics ready (DFRy). Digital forensics readiness (DFR) assists by providing a proactive way for DFI process to be conducted. Artificial intelligence (AI) applications assist in the processing of security incidence reports. This paper proposed the use of un-supervised learning techniques in the field of AI by exploring security threat intelligence reports. AI algorithms are used in the automated analysis of large and complex datasets in intelligence reports thus greatly accelerating the prediction of security incidents in order to provide DFR to the computing environment and anticipated responses for the reduction of security incidents.