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Rahman, Md.Zahidur
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Library & Information Science Neuroscience

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Journal : Mobile and Forensics

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Forensic Artifact Discovery and Suspect Profiling through Google Assistant Rahaman, Abu Sayed Md. Mostafizur; Marzia, Saiyeda; Arnob, Tafsir Haque; Rahman, Md.Zahidur; Akhter, Jesmin
Mobile and Forensics Vol. 5 No. 1 (2023)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v5i1.8046

Abstract

It has become impossible to imagine modern society without the internet and mobile devices dominating our daily lives. As a result, popular apps like Google Assistant, Gmail, Google Home, etc., are quietly entering our veins. People aren't even aware of how much of a digital footprint they leave behind, let alone the fact that it can be completely chronologized and used to put any criminal in jail. The data that we intentionally send to Google is fully retrievable from both the client side (a mobile device) and the cloud. Even if a suspect changes his mobile device, his previous digital footprint still follows him wherever he goes. In this project, we pinpointed the location of the primary database and the major repository for Google Assistant. Here, forensic artifacts of interest from our inquiry have been revealed, including the timeline and copies of previously traded audio chats, as well as a record of deleted data. In addition to that, we have applied the K-means clustering algorithm to isolate the suspect’s voice records and their chronological order among various call records stored in the cloud, where the cluster size is determined using the Silhouette score and the CH index. The findings of the research are to identify forensic artifacts and suspect profiling so that forensic investigators make it easier to conduct criminal investigations
Co-Authors Akhter, Jesmin Arnob, Tafsir Haque Marzia, Saiyeda Rahaman, Abu Sayed Md. Mostafizur