DistLog: A distributed logging scheme for IoT forensics

Abstract Digital forensics are vital in the Internet of Things (IoT) domain. This is due to the enormous growth of cyber attacks and their widespread use against IoT devices. While IoT forensics do not prevent IoT attacks, they help in reducing their occurrence by tracing their source, tracking their root causes and designing the corresponding countermeasures. However, modern IoT attacks use anti-forensics techniques to destroy or modify any important digital evidence including log files. Anti-forensics techniques complicate the task for forensic investigators in tracking the attack source. Thus, countermeasures are required to defend against anti-forensics techniques. In this paper, we aim at securing the IoT log files to prevent anti-forensics techniques that target the logs’ availability and integrity such as wiping and injecting attacks. In the proposed solution, and at regular intervals of time, the logs generated by IoT devices are aggregated, compressed and encrypted. Afterwards, the encrypted logs are fragmented, authenticated and distributed over n storage nodes, based on the proposed Modified Information Dispersal Algorithm (MIDA) that can ensure log files availability with a degree of ( n − t ). For data dispersal, two cases are considered: the case where the fog nodes are interconnected and the case where they are not. For the former case, the n obtained fragments are transmitted to n neighboring IoT devices (aggregation nodes). However, for the latter one, the output is transmitted to the corresponding fog and then, dispersed over the n neighboring fog nodes. A set of security and performance tests were performed showing the effectiveness and robustness of the proposed solution in thwarting well-known security attacks.