NTNU Digital Forensics Group research
NTNU Digital Forensics Group research projects
- Research in the area of large-scale investigations; automatic search through terabytes of electronic data storage within closed systems and the Internet,
- Research and development for the rapid acquisition, correlation and analysis of Internet-related evidence,
- Technologies for cross-media search and data integration to access diverse sources of information, in particular data enrichment from Internet sources,
- Algorithms for the analysis of encrypted evidence and cryptographic credentials,
- Design of advanced computing technologies to achieve more objective evidence analysis and final decision making by implementing computational intelligence,
- Develop of methods and tools for digital penetrator attribution and profiling, visualization of serious criminal relationships and associations, and geographical mapping of digital and physical evidence.
Computational-intelligent Methods used
- Machine Learning and Pattern Recognition: Abstract measurements are classified as belonging to one or more classes, e.g., whether a sample belongs to a known/abnormal class and with what probability, a mathematical model is learnt from examples.
- Data Mining: large volumes of data are processed to discover nuggets of information, e.g., presence of associations, number of clusters, outliers, etc.
- Computer Graphics / Data Visualization: Two-dimensional images or three-dimensional scenes are synthesized from multi-dimensional data for better human understanding,
- Signal / Image Processing: One-dimensional signals and two-dimensional images are transformed for better human or machine processing,
- Computer Vision: Images are automatically recognized to identify objects,
- Robotics: human movements are replicated by a machine.
Overview NTNU Digital Forensics Group projects - current and previous
ArsForensica Workshop 2016