Complex security solutions to detect and prevent threats to cybercrime in the financial sector

01/01/2015 to 31/12/2016

The aim of the project is to develop a comprehensive software solution in the area of detection and prevention of fraudulent behavior in the financial sector, using the latest knowledge in data and predictive modeling, analysis of complex graph structures and dynamic systems and extraction of knowledge from online data sources .

The solution of the project is attended by excellent experts in modeling and algorithmization at FIT CTU, together with experts from Profinit, with many years of experience in software development for the financial sector.

Wednesday, 8 August, 2018


EU to strenghten its expertise in cybersecurity research, technology and industrial developmen

Europe is stepping up its protection against cybersecurity threats, and is discussing a new structure of pool of expertise which will help secure the digital single market and increase the EU’s autonomy in the area of cybersecurity.

Europe is currently working on the establishment of a top knowledge base for cybersecurity and a network of national cybersecurity coordination centres called the European Cybersecurity Industrial, Technology and Research Centre and the Network of National Coordination Centres.

Future Events

Cyber Insurance and its Contribution to Cyber Risk Mitigation - Leiden March 25-29
25/03/2019 to 29/03/2019

The rise in both the scale and severity of recent cyberattacks demands new thinking about cybersecurity risk and the mitigation and transfer of that risk. Cyber insurance is one potential way to manage risk by transferring damage liability, but the cyber insurance market is immature and the understanding and actuarial knowledge of cyber-risk is currently underdeveloped.

e-SIDES workshop 2019

e-SIDES workshop: Towards Value-Centric Big Data: Connect People, Processes and Technology


2 April 2019

10am to 4pm


e-SIDES is a research project funded by European Commission H2020 Programme that deals with the ethical, legal, social and economic implications of privacy-preserving technologies in different big data context.