The Florida State University Research Foundation, Inc.

Sam Houston State University

Umit Karabiyik

Sudhir Aggarwal

Gokila Dorai

Tathagata Mukherjee

Nicholas A Guerra

Manuel Hernandez-Romero

James Parsons

Khushboo Rathi

Many mobile devices are used for documenting different scenarios that are encountered by the users as they go about their daily lives. In many situations, a mobile device may be used to document the scenario. This data may be of significant forensic interest to an investigator. In many situations, the owner of the phone may be willing to provide the investigator access to this data (through a documented consent agreement). Such consent is usually contingent upon the fact that not all the data available on the phone may be extracted for analysis, either due to privacy concerns or due to personal reasons. Courts have also opined in several cases that investigators must limit data extracted, so as to focus on only 'relevant information' for the investigation at hand. Thus, only selective (or filtered) data should be extracted as per the consent available from the witness/victim (user). Described herein is the design and implementation of such a targeted data extraction system (TDES) for mobile devices. The TDES assumes consent of the user and implements state of the art filtering using machine learning techniques. This system can be used to identify and extract selected data from smart phones, in real time at the scene of the crime.

Targeted data extraction system and method

Growing community of inventors

Huntsville, TX, United States of America

Umit Karabiyik