RAMSES

Description

• Programme: Horizon 2020, Fight Against Crime and Terrorism (SC7)
• Period: 09/2016-08/2019
• Funding amount: €3.8 million, of which €367,000 for Bavaria
• Coordinator: Treelogic Telemática y Lógica Racional para la Empresa Europea, S.L., Spain
• Website: www.ramses2020.eu

The rate of internet crime is increasing all the time. The web allows criminals to hide their identity, thus making it easier to commit theft and fraud. The objective of RAMSES (Internet Forensic platform for tracking the money flow of financially-motivated malware) is to design and develop a holistic, intelligent, scalable and modular platform for law enforcement agencies to facilitate digital forensic investigations.

The system being developed by RAMSES (Project ID 700326) will extract, analyse, link and interpret information extracted from the internet relating to financially-motivated malware. The project is focused on two types of malware: ransomware, which encrypts data and demands money for decrypting it, and banking trojans, which spy on online banking data. The project team uses state-of-the-art technologies: using big data analysis and visualisation tools, the platform will be able to search not only the public “surface web”, but also the hidden, not readily accessible “deep web”. The new solution will detect manipulations and hidden information in images and videos, locate and analyse different malware programs and track payments demanded by malware. The project involves developers and users, but also victims of malicious software, in order to get a better understanding of when and how malware is distributed. The platform will be tested during the course of the project in collaboration with law enforcement authorities in Portugal, Belgium and Spain. RAMSES will use both open-source and commercial software. The software developed in the project will be available free of charge to law enforcement authorities that have registered with RAMSES. Potential future marketing models will be examined as part of the project, supported by a feasibility study on the evaluation of factors for adoption of the platform by end-users.