DSpace Repository

Evaluating Factors Responsible for Inconsistencies in Mobile Devices Digital Forensic Evidence Extraction Process Model

Show simple item record

dc.contributor.author Gilbert, Gilibrays Ocen
dc.contributor.author Mutua, Stephen
dc.contributor.author Mugeni, Gilbert Barasa
dc.contributor.author Karume, Simon
dc.contributor.author Matovu, Davis
dc.date.accessioned 2023-11-07T10:07:42Z
dc.date.available 2023-11-07T10:07:42Z
dc.date.issued 2019
dc.identifier.issn 2454-132X
dc.identifier.uri https://repository.cuk.ac.ke/handle/123456789/1147
dc.description An abstract published in the International Journal of Advance Research, Ideas and Innovations in Technology en_US
dc.description.abstract The proliferation of mobile devices has revolutionized life in the 21st century ranging from the way people socialize to the modes of doing business. Mobile devices contain substantial amounts of private data that in event of crime or security investigations when adduced before any court of law can aid in resolving a number of undetermined causes. However, mobile digital forensics research is still faced with several challenges. Most existing mobile devices digital forensic evidence extraction models are vendor-specific and thus anchored on specific device platforms such as Android, Windows, Apple iOS, and Blackberry. Additionally, these models contain various process inconsistencies and lack specified technical documentation. Further, the growing demand for mobile devices and crime-related occurrences affecting them has strained and exposed the existing models. A number of questions thus remain unanswered into the factors responsible for these inconsistencies and the lack of a unified model that can be applied across these four operating system platforms. A mixed-method approach involving a survey was used in this study where respondents were drawn from ICT practitioners, law enforcement agencies, researchers and the business community. This study highlights several factors that contribute to digital evidence extraction process model inconsistencies which include policy, extraction methods, nature of data, device type, data type, and extraction tools among others. The study proposes systematic documentation of every step followed during evidence extraction from mobile devices so as to avert the inconsistencies. en_US
dc.language.iso en en_US
dc.publisher International Journal of Advance Research, Ideas and Innovations in Technology. en_US
dc.relation.ispartofseries Volume 5;Issue 6
dc.subject Mobile devices en_US
dc.subject Digital evidence en_US
dc.subject Process model en_US
dc.subject Extraction inconsistencies en_US
dc.title Evaluating Factors Responsible for Inconsistencies in Mobile Devices Digital Forensic Evidence Extraction Process Model en_US
dc.type Other en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account