Digital Forensic Investigation Report3/20/2021
IFIP International Federation for Information Processing 2013.
Digital Forensic Investigation Report Download Citation CopyRequest full-text Download citation Copy link Link copied Request full-text Download citation Copy link Link copied To read the full-text of this research, you can request a copy directly from the authors.Citations (9) References (16) Abstract Due to the lack of standards in reporting digital evidence items, investigators are facing difficulties in efficiently presenting.The authors focused on developing a standard digital evidence items by surveying various digital.Research results enabled the authors in creating a defined XML schema for digital evidence. As the forensic consummation for the whole effort, the AFC test does not call for or provide a structure to collate and present the final results which are available at the end of its comparison phase. Because of the absence of a structured format of collecting the results, the structuring and presentation of the result by experts may lack logical patterning and expert-independent consistency (Bariki, Hashmi, and Baggili, 2010). Unlike the AFC test, the POSAR test has a reporting phase which helps and encourages the cyber forensic expert to collect and collate the results concerning similarities and commonalities in a structured manner, statistically as well as verbally.. Forensics of Software Copyright Infringement Crimes: The Modern POSAR Test Juxtaposed With The Dated AFC Test Article Jan 2014 Vinod Bhattathiripad View. Object types encapsulate these fields making items placed in them close to mutually exclusive, but like the prior example there lacks details that help experts enter data on cyber items (files, processes etc.). Conventions are especially lacking with respect to presentation of evidence in courts (Bariki et al., 2011).. CuFA: A more formal definition for digital forensic artifacts Article Full-text available Aug 2016 DIGIT INVEST Vikram S. Harichandran Daniel Walnycky Ibrahim Baggili Frank Breitinger The term artifact currently does not have a formal definition within the domain of cyberdigital forensics, resulting in a lack of standardized reporting, linguistic understanding between professionals, and efficiency. In this paper we propose a new definition based on a survey we conducted, literature usage, prior definitions of the word itself, and similarities with archival science. This definition includes required fields that all artifacts must have and encompasses the notion of curation. Thus, we propose using a new term curated forensic artifact (CuFA) to address items which have been cleared for entry into a CuFA database (one implementation, the Artifact Genome Project, abbreviated as AGP, is under development and briefly outlined). An ontological model encapsulates these required fields while utilizing a lower-level taxonomic schema. We use the Cyber Observable eXpression (CybOX) project due to its rising popularity and rigorous classifications of forensic objects. Additionally, we suggest some improvements on its integration into our model and identify higher-level location categories to illustrate tracing an object from creation through investigative leads. Finally, a step-wise procedure for researching and logging CuFAs is devised to accompany the model. Finally, Bariki, et al. They surveyed the reporting functionality of three tools, including EnCase and FTK, and note the variations in the evidentiary items included in the reports.. Comparison of the Data Recovery Function of Forensic Tools Conference Paper Jan 2013 Joe Buchanan-Wollaston Tim Storer William Glisson Commercially-available digital forensic tools are often large, expensive, complex software products, offering a range of functions to assist in the investigation of digital artifacts. Several authors have raised concerns about the reliability of evidence derived from these tools. This is of particular importance because many forensic tools are closed source and, therefore, are only subject to black box evaluation. ![]() This paper compares - rather than individually evaluates - the data recovery function of two forensic suites and three standalone non-forensic commercial applications. ![]() However, some variation exists in the data recovered by the tools.
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