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Making digital evidence presentable is hard due to its intangible and complex nature and the variety of targeted audiences. In this paper, we present Digital Forensic Knowledge Graph (DFKG) for visualizing and reasoning about digital forensic evidence. We first describe the criteria of presentable evidence to ensure the authenticity, integrity, validity, credibility, and relevance of evidence. Then we specify DFKG to capture presentable forensic evidence from three perspectives: (1) the background of a criminal case, (2) the reconstructed timeline, and (3) the verifiable digital evidence related to the criminal activity timeline. We also present a case study to illustrate the DFKG-based approach. 

This paper presents a systematic approach to designing digital forensics instructional materials to address the severe shortage of active learning materials in the digital forensics community. The materials include real-world scenario-based case studies, hands-on problem-driven labs for each case study, and an integrated forensic investigation environment. In this paper, we first clarify some fundamental concepts related to digital forensics, such as digital forensic artifacts, artifact generators, and evidence. We then re-categorize knowledge units of digital forensics based on the artifact generators for measuring the coverage of learning outcomes and topics. Finally, we utilize a real-world cybercrime scenario to demonstrate how knowledge units, digital forensics topics, concepts, artifacts, and investigation tools can be infused into each lab through active learning. The repository of the instructional materials is publicly available on GitHub. It has gained nearly 600 stars and 22k views within several months. Index Terms