This awardee has received supplemental funding. This award detail page includes information about both the original award and supplemental awards.
Description of original award (Fiscal Year 2006, $399,836)
University of Rhode Island will synthesize existing Steganography detection techniques into a cohesive software suite. In addition, University of Rhode Island will perform research to augment existing tools, improving computational power and efficiency through techniques including parallel computing on high-performance clusters. To decrypt steganographic files, this project will develop parallel password cracking techniques. The result of this project will be a prototype automated software module for the popular Encase computer forensic tool. This module will integrate Steganography detection, decryption, and original document extraction, as well as be available as a web service to allow law enforcement access to a high-performance parallel cluster for Steganography detection and breaking via the Internet.
Steganography is a growing concern for law enforcement because it compounds issues posed by encrypted evidence with the complicating factor that encrypted data is hidden behind an innocuous façade. Furthermore, the many steganographic algorithms and programs readily available facilitate their criminal use. Although there has been some work in steganography
detection and breaking, there is currently no single easy-to-use tool available to law enforcement.
This project will continue the University of Rhode Island work in steganography detection by extending it to media such as MP3 and video, and by producing software packages for dissemination.
This project attempts to address the BJS 2002 forensic backlog in the area of computer crime.
This project contributes to the reduction of DNA backlog via the following approach:
' Automated Steganography Detection will increase the likelihood of detecting steganography and extracting the evidence hidden using this technology.
' Automated Steganography Detection will allow analysts to process evidence more efficiently; therefore, reducing the backlog of cases.