1. A summary of the report written by W. Alink, R.A.F. Bhoedjang, P.A. Boncz, and A.P. de Vries.

2. The Problem Large amount of data – possibly terabytes Limited amount of time Higher chance of missing traces Diversity of data Too many specialized tools Difficult to integrate results Time constraints Knowledge constraints

3. Solution Separate feature extraction from analysis: Feature Extraction: The extraction of useful features from raw data- Includes more than just file data Analysis: Browsing, querying and correlating. One output format for forensic analysis tools (based on XML) XML for storing and querying the output of the tools. Automate feature extraction Various current projects in law enforcement community related to automated feature extraction

4. XIRAF Prototype system that uses this approach “XML Information Retrieval Approach to digital Forensics” Automatic feature extraction from disk image/s Stores data in XML database Uses XQuery (XML query language) to access the database and the data from the disk-image.

5. Framework 3 components: Tool repository: feature extraction tools Feature extraction manager: manages the invocation of the tools, merges output and stores it in storage subsystem. Storage subsystem: composed of raw evidence (binary large objects) and extracted features (XML)

6. General Overview of process Image fed to system (binary data) Feature Extraction Manager extracts useful features (uses tool repository) Feature Extraction Manager stores features in single XML document (in form of a tree). The Feature Extraction Manager can then run other tools on the found data and add to the xml document. Data stored in storage sub system, where the binary data or the XML tree can be accessed

7. Forensic Applications Timeline browser Mainstream tools do file-system browsing (relies on file- system meta-data) This application of XIRAF can get all XML fragments with a timestamp, gathered from different tools (which could include things like chat logs). Photo search Finds digital images that meet desired conditions Can consider camera model, date and time of recording, image resolution and more.

8. Forensic Applications Child Pornography Detection Uses hash of various files that are known to contain child pornography Matches files against a database of hashes The hash database is converted to XML, and preloaded into the XML database XIRAF contains. The comparison is done during the feature extraction phase.

9. Conclusion/future work Too early to draw definitive conclusions (just a prototype) An increasing number of tools have started producing output in XML. Mobile phone queries More knowledge bases

10. References W. Alink, R.A.F. Bhoedjang, P.A. Boncz, and A.P. de Vries. ““XIRAF – XML-based indexing and querying for digital forensics”. Available at: http://dfrws.org/2006/proceedings/7-Alink.pdf http://dfrws.org/2006/proceedings/7-Alink.pdf