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Gokila Dorai, PhD - Augusta University. Augusta, GA, US

Gokila Dorai, PhD Gokila Dorai, PhD

Assistant Professor | Augusta University

Augusta, GA, UNITED STATES

Dr. Dorai’s area of expertise is mobile/IoT forensics research and developing a targeted data extraction system for digital forensics.

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Gokila Dorai - FSU Doctoral Student (Computer Science) - Digital Narratives Tech N' Talk # 6: Tensorflow on OpenShift with Gokila Dorai and Eleanor Mehlenbacher Identification and Extraction of Content-hiding iOS Applications by Dr. Gokila Dorai

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Biography

Dr. Gokila Dorai is an Assistant Professor in the School of Computer and Cyber Sciences (SCCS) at Augusta University (AU). Dr. Dorai’s area of expertise is mobile/IoT forensics research. She is passionate about inventing digital tools to help victims and survivors of various digital crimes.

Areas of Expertise (6)

Algorithms

Mobile Computing

loT forensics research

Mobile Research

Digital Crimes

Software Development

Education (3)

Florida State University: Ph.D., Computer Science & Mobile Forensics 2019

Florida State University: M.S., Computer Science 2016

R.M.K. Engineering College: B.E., Computer Science & Engineering 2007

Articles (6)

VIDE - Vault App Identification and Extraction System for iOS Devices

Forensic Science International: Digital Investigation

2020 Content hiding (or vault) apps are a class of applications that allow users to hide photos, videos, documents and other content securely. A subclass of these applications called decoy apps further supports secret hiding by having a mode which mimics standard apps such as calculators but can turn into a vault app through entering a specific input. In this work we focus on iOS devices and first describe how to identify content hiding applications from the App Store. We consider not only the US Store but also give results for App Stores in Russia, India and China. We show an effective and very fast identification of content hiding apps through a two-phase process: initial categorization using keywords followed by more precise binary classification. We next turn to understanding the behavior and features of these vault apps and how to extract the hidden information from artifacts of the app's stored data.

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Data Extraction and Forensic Analysis for Smartphone Paired Wearables and IoT Devices

Internet of Things: Providing Services Using Smart Devices, Wearables, and Quantified Self

2020 Wearable devices and Internet of Things (IoT) devices have marked the beginning of a new era in forensic science. Data from smart home gadgets and wearable devices can serve as an important "witness" in civil as well as criminal cases. Thus data extracted from these devices has started to impact and transform litigation. Data collected from wearable devices can help determine truths in witness testimony since these devices document several types of activities of an individual at all times. Increased use of smart home devices also opens a new window for investigators.

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Analysis of iOS SQLite Schema Evolution for Updating Forensic Data Extraction Tools

2020 8th International Symposium on Digital Forensics and Security (ISDFS)

2020 Files in the backup of iOS devices can be a potential source of evidentiary data. Particularly, the iOS backup (obtained through a logical acquisition technique) is widely used by many forensic tools to sift through the data. A significant challenge faced by several forensic tool developers is the changes in the data organization of the iOS backup. This is due to the fact that the iOS operating system is frequently updated by Apple Inc. Many iOS application developers release periodical updates to iOS mobile applications.

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A Targeted Data Extraction System for Mobile Devices

IFIP International Conference on Digital Forensics

2019 Smartphones contain large amounts of data that are of significant interest in forensic investigations. In many situations, a smartphone owner may be willing to provide a forensic investigator with access to data under a documented consent agreement. However, for privacy or personal reasons, not all the smartphone data may be extracted for analysis. Courts have also opined that only data relevant to the investigation at hand may be extracted.

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Building Tools for Forensic Analysis of Mobile and IoT Applications Using Selective Data Extraction

Florida State University

2019 The amount of data stored on smart phones and other mobile devices has increased phenomenally over the last decade. As a result there has been a spike in the use of these devices for documenting different scenarios that are encountered by the users as they go about their daily lives. Smart phone data has also become a critical evidence in the court for several criminal cases.

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I Know What You Did Last Summer: Your Smart Home Internet of Things and Your iPhone Forensically Ratting You Out

ARES 2018: Proceedings of the 13th International Conference on Availability, Reliability and Security

2018 The adoption of smart home Internet of Things (IoT) devices continues to grow. What if your devices can snitch on you and let us know where you are at any given point in time? In this work we examined the forensic artifacts produced by Nest devices, and in specific, we examined the logical backup structure of an iPhone used to control a Nest thermostat, Nest Indoor Camera and a Nest Outdoor Camera. We also integrated the Google Home Mini as another method of controlling the studied Smart Home devices.

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