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Provides a mobile digital forensics triage device that is cost-effective, easy to use, and provides results quickly.

Challenges

Provide the DoD and law enforcement with a cost-effective field-ready digital forensics triage device.

1) Quickly scans high-capacity digital media devices for both unstructured and structured data.

2) Delivers a low-cost solution without sacrificing enhanced performance capabilities.

3) Provides a NIST-compliant device that maintains the chain of evidence.

4) Designed specifically for on-scene, time-sensitive investigations.

5) Supports fast, targeted feedback for immediate evidence assessment.

6) Prevents over-collection and large backlogs at digital forensics labs worldwide.

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The GBL Systems Corporation Solution

Provide the DoD and law enforcement with a cost-effective field-ready digital forensics triage device.

CyberFITT™ is a portable handheld field-ready digital forensics triage tool designed for on-site assessment of digital storage devices that are subject to be searched or investigated to supply rapid intelligence to DoD, other agencies, and law enforcement personnel. GBL is developing this product leveraged research from the University of Southern California (USC) and California State University Channel Islands (CSUCI). CyberFITT provides a digital forensics triage process that is easy to understand, simple to use, and quick to provide results.  It is built in a small, portable, self-powered case that can be deployed anywhere to analyze digital media, find contraband, and allow security-enabled closed-loop Wi-Fi access to the results.  This addresses the need for a low-cost solution to deliver automated searching using Machine Learning algorithms for digital forensic purposes.

CyberFITT delivers the following technologies: 1.) Machine Learning (ML) Cyber Forensics ecosystem for automatic identification of contraband in image files utilizing the latest AI technology (Google Coral, TensorFlow, Neural Network), 2.) Latest Linux-based system infrastructure to maximize file throughput and utilize standard web front-end technologies (React), 3.) Wi-Fi enabled access via secure WPA2 and least-privilege guidelines, 4.) Creation of a mobile application that enables results retrieval, CyberFITT administration, and additional custom searches, allowing multiple personnel onsite to connect to CyberFITT simultaneously.

Benefits

CyberFITT quickly searches media (using built-in artificial intelligence) when those devices are plugged into the CyberFITT module.

Advanced Search Capabilities

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CyberFITT provides extremely fast search capabilities for any digital media device (hard drives, thumb drives, smart mobile devices, drones, etc.) for mission-specific content.

Mobile Field Deployment

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Lightweight, battery-powered, multi-user enabled, secure, and ready for mobile field deployment.

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Rapid Reporting

Media Device Prioritization

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Enables prioritization of large amounts of media devices for detailed searches using built-in artificial intelligence to search voice content, text, or images for instance drugs, guns, or money.

Creates a report of all findings in a session of use, with iPhones, Android phones, and most common drive formats read capabilities.

Flowchart illustrating a machine learning cybersecurity ecosystem. It shows digital evidence like hard drives, smartphones, cameras, and USB drives feeding into CyberFIT, which analyzes info, images, and files. CyberFIT connects to a training datalake with datasets from various sources and cloud services like Google, Colab, and AWS. Results are used by agencies and investigators, represented by a smartphone and tablet.

CyberFITT Features

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Supports Chain-of-Custody Documentation Record

Enforces a structured procedure and approach that is user-friendly to non-digital forensic trained investigators by use of simple instructions ease of searching the devices.

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Provides Immediate Evidence Assessment

Enables investigators a very fast digital evidence overview into the types of files and information stored on the computer equipment at the site of the search warrant.

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Prioritizes Collection of Relevant Data for Analysis

Automated analysis focuses on data & device collection, thereby reducing the volume of data sent for lengthy in-depth lab analysis.

Get started with GBL Systems Corporation solutions on AWS

To learn more about CyberFITT, please download the corresponding brochure here.

Case Studies

Case Study 1: Southern California High Tech Task Force (SCHTTF)*

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Challenges

The SCHTTF division of the Ventura County District Attorney’s Office was seeking a highly portable, inexpensive, efficient mobile device intended to overcome the need for a fully digital lab equipment device to be brought into the field.

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Solution

GBL’s CyberFITT technology was deployed by the SCHTTF in the Ventura Digital Forensics Lab, where it was tested during the execution of search warrants.

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Status/Results

CyberFITT acquired digital media content and enabled analysis by investigators via Wi-Fi, collecting potential digital evidence without the fear of tainting the evidentiary integrity. As an auditing feature, CyberFITT also kept a separate log of devices that were collected.*

* Dept of Navy endorsement is not implied, collaborative efforts conducted under Cooperative Research and Development Agreement N63394-22-0003 with the Naval Surface Warfare Center, Port Hueneme Division.


Case Study 2: Advanced technology demo for Surface Navy ISEA and Fleet Support

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Challenges

Provide the Navy equipment that is fully-digital and portable to be brought into the field, that allows numerous personnel at once to search multiple media devices (hard drives, USB, etc.) supporting structured and unstructured data.

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Solution

Provide a demonstration of CyberFITT, including the forensic analysis of digital data (disks, thumb drives, laptops) and identifying previously flagged images or key terms at the FATHOMWERX/ANTX-Coastal Trident.

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Status/Results

CyberFITT hardware form factor modified for Navy use case. Successfully applied the CyberFITT ML Ecosystem to search for weapons in pictures on multiple digital media devices. In the process of assessing CyberFITT’s search metrics.