For reliable digital evidence to be admitted in a court of law, it is important to apply
scientifically proven digital forensic investigation techniques to corroborate a suspected …

Abstract Machine learning has been shown as a promising approach to mine larger
datasets, such as those that comprise data from a broad range of Internet of Things devices …

Database forensic investigation (DBFI) is an important area of research within digital
forensics. It's importance is growing as digital data becomes more extensive and …

Internet of Things Forensics (IoTFs) is a new discipline in digital forensics science used in
the detection, acquisition, preservation, rebuilding, analyzing, and the presentation of …

Abstract Internet of Things (IoT) are becoming commonplace in homes, buildings, cities, and
nations, and IoT networks are also getting more complex and interconnected. The …

Abstract User and Entity Behaviour Analytics (UEBA) mechanisms rely on statistical
techniques and Machine Learning to determine when a significant deviation from patterns or …

Currently, about half of all global enterprises are adopting and using some form of cloud
computing services. In cloud computing, potential digital evidence is distributed across …

Fraud detection in the fintech sector is a critical area of concern as financial transactions
increasingly shift to digital platforms. This paper presents a comprehensive analysis of …

Network Forensics (NFs) is a branch of digital forensics which used to detect and capture
potential digital crimes over computer networked environments crime. Network Forensic …

Abstract A Cloud Forensic Readiness as a Service (CFRaaS) model allows an environment
to preemptively accumulate relevant potential digital evidence (PDE) which may be needed …