at the Faculty of Electrical Engineering, Mathematics, and Computer Science

The Cybersecurity group conducts research into various topics, ranging from cryptography to data analytics, and focuses on improving cybersecurity. We aim to make – in particular the digital – world safer by furthering state-of-the-art computer science theories, algorithms, and implementations.

Research area

In privacy, we develop advanced methods for homomorphic encryption and multi-party computing with application in data sharing and blockchain. In hardware, we use machine learning to develop new attack mechanisms for side-channel analysis, and evolutionary algorithms to create improved hardware designs. In networking, we build crawlers and fuzzers to collect big data sets that give us an overview of the latest security threats. In software, we develop new algorithms for automated reverse engineering or analysis of applications.

We develop solutions that contribute to the very latest technology in the fields of computer security and artificial intelligence (AI). Examples include the development of learning algorithms that can handle large network data flows, deep learning methods that are immune to common side-channel defenses, machine learning algorithms that can operate on encrypted data, and analysis of the latest security threats. We aim to publish our results in scientific journal and conferences of A and A* quality, and to transfer our scientific know-how and technologies to students, and our public and private partners in the field of cybersecurity.


We are responsible for cybersecurity education at B.Sc. and M.Sc. level in the computer science program. Since 2013, a specialization program on cybersecurity exists within the master program in Computer Science. We closely collaborate in teaching, student supervision and research with other groups within Computer Science (such as Software Engineering, Distributed Systems, and Delft Blockchain lab), and in particular with our colleagues in the Cybersecurity group at the Faculty of Technology, Policy and Management through the Computer Science special program Cybersecurity, and the Executive Master program Cybersecurity.

Collaborations with external organizations are essential for education and research in cybersecurity. The cybersecurity group has an extensive network of public and private partnerships, which in many cases provide us with use cases, cybersecurity data, and financial support. Our research and education can therefore be characterized as being use-inspired and fundamental, ranging from developing new security and AI algorithms to engaging with real use cases of our partners.


Research activities
The research activities are organized around our faculty members.


15 September 2020

Test of Time Award for CYS paper

09 September 2020

Apostolis Zarras will join CYS as of November 1, 2020

11 May 2020

The Information Forensics and Security Technical Committee: Then, Now, and in the Future

The Information Forensics and Security Technical Committee (IFS-TC) is one of the 13 TCs in the IEEE Signal Processing Society (SPS). Its overarching mission is to foster and lead scientific and technological development in all aspects related to forensics and security in our society.

05 April 2020

Number of bitcoins captured from exchange hacks are decreasing

22 March 2020

Dr. Kaitai Liang joins Cyber Security Delft

27 February 2020

IEEE Open Journal on Signal Processing

12 December 2019

The 11th edition of IEEE International Workshop on Information Forensics and Security took place at Science Center between December 9 and 12

05 November 2019

Azqa Nadeem

Azqa Nadeem has been nominated for TU Delft Best Graduate 2019

15 October 2019

4TU.Federation NIRICT registration support for Master of Science students in the Netherlands

We gladly announce that 4TU.Federation Netherlands Institute for Research on ICT (NIRICT) is supporting IEEE Workshop on Information Forensics and Security to be held in Delft, December 9-12.

03 September 2019

Victory at the Robust Malware Detection Challenge

Our team won both tracks of the Robust Malware Detection Challenge hosted by the Adversarial Machine Learning Workshop at KDD 2019.