Umit Karabiyik, an assistant professor of computer science and information technology at Purdue University’s Polytechnic Institute, often conducts research inspired by nearly 10 years of experience working with law enforcement. More recently, he has focused on data that ordinary citizens voluntarily choose to provide to law enforcement – specifically, photos, videos, text messages and other data from cellphones – and on the how to collect this data in a way that encourages individuals to help. law enforcement while maintaining personal privacy and security.
Karabiyik thinks most people would love to help law enforcement solve a crime, but may be hesitant to share everything on their personal devices.
“We want to help, but we may also have images or data on our phones that we don’t want to share with others,” Karabiyik explained. “An answer to this dilemma may be an app that allows us to securely and confidently share only what we choose to share.”
Karabiyik’s latest work will target device data sharing during mass incidents – when law enforcement asks hundreds of witnesses or victims to provide data related to a specific event, such as a bombing in the bomb. App-based solutions that allow individuals to consent and only share certain data from their phones could make it much easier for law enforcement to access the information they need to advance an investigation or solve a crime. crime.
Law enforcement apparently agrees with Karabiyik’s approach; he recently received two separate research grants from the Department of Justice totaling more than $875,000 for projects that include the development of a new mobile-focused forensic intelligence platform and the creation of a program for harness data collected by fitness devices and smartwatches to train criminal justice professionals.
Award: Scalable Multiphone Targeted Data Extraction System
Total funding to date: $600,984
Awarded by: National Institute of Justice, Ministry of Justice
This project will further develop an existing system, the Targeted Data Extraction System (TDES), originally created to extract case-specific data in a forensic manner from the mobile device of volunteer participants. A new “Forensic Intelligence” platform will augment TDES with significant new capabilities and use artificial intelligence (AI) to make the entire platform more efficient and convenient for law enforcement. Ultimately, this project will focus on creating a scalable multi-phone data extraction system with forensic intelligence capabilities, labeled SM-TDES, to provide forensic intelligence during mass incidents like the Boston Marathon bombing or the Aurora mass shooting.
“We want to highlight and explore the need to extract data from many phones, simultaneously, after an incident involving many people,” Karabiyik explained. “We will also develop AI-based analytics capabilities to automatically extract relevant information that will provide viable leads for law enforcement in these mass incident cases.”
Participating researchers include Umit Karabiyik, Sudhir Aggarwal from Florida State University and Tathagata Mukherjee from the University of Alabama at Huntsville.
Award: internet of things
Total funding to date: $297,967
Awarded by: Justice Support Office, Ministry of Justice
This project focuses on evidence-based data collected by Internet of Things (IoT) devices, specifically wearable fitness devices and smartwatches &nmash; and stored in the cloud. Working with the National White Collar Crime Center (NWC3), Karabiyik and a team of Purdue University researchers will also create training and technical assistance, including in-person and virtual sessions, to help criminal justice professionals with legal models, technical information on fitness equipment and their capabilities, examples of courtroom exhibits, and databases and online resources.
“This training program we are developing will support criminal investigators, digital forensics examiners and prosecutors who encounter IoT evidence,” said Karabiyik, who acts as the project’s lead investigator.
Participating researchers include Purdue’a Karabiyik, Smriti Bhatt, assistant professor of cybersecurity, and Marcus Rogers, assistant dean for cybersecurity initiatives, as well as Steve DeBrota, Chuck Cohen and Robert Leazenby of NW3C (the National White Collar Crime Center).
Karabiyik’s research interests include digital and cyber forensics, forensic intelligence, and machine learning applications in cybercrime and security. In addition to his research and teaching responsibilities, he is an associate editor of the Journal of Digital Forensics, Security and Law and a junior member of the editorial board of the Journal of Surveillance, Security and Safety.