SIMARGL
SIMARGL is a project that will help to combat the pressing problem of malware. It aims to tackle the new challenges in the cybersecurity field, including information hiding methods, network anomalies, stegomalware, ransomware and mobile malware. SIMARGL will offer an integrated and validated toolkit improving European cybersecurity.
SIMARGL will use breakthrough methods and algorithms to analyze the data from networks, such as: concept drift detectors, advanced signal processing and transformations, lifelong learning intelligent systems (LLIS) approach, hybrid classifiers, and deep learning, just to mention some techniques.
PREVISION
PREVISION partners will take advantage of their capabilities, expertise and previously delivered research, together with already defined and emerging standards and best practices in Europe, so as to focus their resources and attention to the new elements and novel aspects of the project. The overall strategy in the execution of the PREVISION project is based on an iterative development methodology, which involves frequent software releases being made available to the LEA and practitioners end-users for testing and evaluation, resulting in keeping them continuously in the production loop. The PREVISION Platform will be deployed in 10 different demonstrations, managed by the different LEAs and practitioners of the consortium.