Content-Based Image Retrieval for Digital Forensics

Digital forensic investigators are often faced with the task of manually examining a large number of (photographic) images in order to identify potential evidence. The task can be especially daunting and time-consuming if the target of the investigation is very broad, such as a web hosting service. Current forensic tools are woefully inadequate in facilitating this process and are largely confined to generating pages of thumbnail images and identifying known files through cryptographic hashes. We present a new approach that significantly automates the examination process by relying on image analysis techniques. The general approach is to use previously identified content (e.g., contraband images) and to perform feature extraction, which captures mathematically the essential properties of the images. Based on this analysis, we build a feature set database that allows us to automatically scan a target machine for images that are similar to the ones in the database. An important property...

• Type: Conference
• Year: 2005
• Where: IFIP
• Authors: Yixin Chen, Vassil Roussev, Golden G. Richard III, Yun Gao
• Keywords: Communications, Contraband Images, Feature Set, IFIP 2005, Image