New automated digital media detection and categorization plus computer forensic data ingestion capabilities, integrates and analyses critical digital evidence sources including social media, cloud, computer, mobile and cellular operator data into a single view to expedite evidence analysis
Cellebrite, the leading provider of digital intelligence solutions, has announced groundbreaking enhancements to its Analytics offerings designed to detect and analyze digital media evidence faster using a series of machine learning algorithms. This latest advancement in digital evidence analysis provides law enforcement professionals with cutting edge neural network-based algorithms that automatically identify and categorize previously known and unknown images and video clips.
Access to advanced analytic tools for text, video, and images optimizes investigative resources by eliminating manual analysis of large volumes of media artifacts and helps to reduce the psychological stress of reviewing sensitive material typically involved in criminal cases.
“Digital evidence from mobile phones, social media accounts, and computers can carry hundreds of data artifacts that include image and video meta data and classification, which can make manual evidence analysis even more complex and time consuming,” said Patrick Krieg, Detective Sergeant-Criminal Investigation Division Dunwoody Police Department. “Using intelligence obtained in merely hours from Cellebrite Analytics allowed my investigative unit to pursue leads that may have otherwise took weeks or months to locate. The depth of this tool and its ability to cross-reference and identify significant target correlations is unprecedented. I found that this analytic tool finally offered a viable solution to the massive amount of information obtained through cellular extractions and applying that information to a usable and presentable format.”
This new release of Cellebrite’s UFED Analytics Platform provides powerful options for correlating, viewing and exploring files from various computer, social media, cloud, mobile, cellular operator records and other digital data sources in a centralized view, with managed access for multiple users, providing real digital intelligence and collaboration for investigative teams. Key updates to the platform include —
– Automated Image Matching and Categorization: This first-of-its-kind capability automatically categorizes images and individual video frames to eliminate manual review of duplicative evidence and correlate unknown images as well as identify unique media so investigative teams can focus on the data of interest. State-of-the-art algorithms have been deployed to automatically detect objects such as weapons and drugs within media. The system also detects and categorizes child pornography, adult content, documents and screen shots resulting in accelerated access to investigation relevant media.
– Face Recognition and Matching: The unique algorithms used for automatic detection of faces within any picture or video available to the system, allow investigators to quickly and accurately cross-match individual faces in media.