Cybersecurity
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.
Education
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.
News
01 juni 2022
Invited talk by Dr. Zeki Erkin at National Cyber Security Center
“Cyber Threat Intelligence" Invited talk by Dr. Zeki Erkin at National Cyber Security Center June 2, 11:30 online.
01 juni 2022
ESORICS 2023 Conference announced
We are pleased and exciting to announce that one of the European largest computer security conferences, ESORICS, will be organized by the EEMCS cybersecurity group, in September 2023.
31 mei 2022
Cyber Security Webinar by Dr. Giovanni Apruzzese – Some pragmatic relationships between Machine Learning and Cybersecurity
In this talk, I will discuss two recent research efforts that will be presented in the next weeks at IEEE SPW DLS, and IEEE EuroSP.
03 mei 2022
Call for Nominations – Best Cybersecurity Master Thesis (BCMT) Award in the Netherlands 2020-2021
The Cyber Security next generation is a community-building activity in the Netherlands in the field of Cybersecurity. One of the main goals of CSng is to form the next generation of researchers and engineers in Cybersecurity. To this end, CSng has decided to establish an award for the best Master thesis in this field. This is the fourth edition of the award where we are calling for the nomination of excellent Master students who graduated with an outstanding thesis in Cybersecurity.
11 april 2022
PAM 2022 Best Paper Award: "Old but Gold: Prospecting TCP to Engineer and Live Monitor DNS Anycast"
Dr. Giovane C. M. Moura (Cybersecurity group and SIDN Labs) and colleagues from the University of Southern California/Information Science Institute (UCS/ISI) paper "Old but Gold: Prospecting TCP to Engineer and Live Monitor DNS Anycast" has won the Best Paper Award in the Passive and Active Measurement Conference 2022 (PAM2022).
04 april 2022
14th International IEEE Workshop on Information Forensics & Security
On the behalf of Organizing Committee, it is our great pleasure to invite you to the 14th IEEE International Workshop on Information Forensics and Security (WIFS) 2022 that will be held 12th -16th December 2022 in Shanghai, China.
08 maart 2022
CYS group co-organises SecureComm2022
The Cybersecurity Group at the Faculty of Electrical Engineering, Mathematics, and Computer Science will organise the 18th EAI International Conference on Security and Privacy in Communication Networks (SecureComm2022) with the University of Kansas, U.S. SecureComm is a conference in EAI core conference portfolio focusing on cybersecurity.
15 december 2021
Dr. Zeki Erkin elected as vice-chair for IEEE Information Forensics and Security Technical Committee
Dr. Zeki Erkin is elected as vice-chair for IEEE Information Forensics and Security Technical Committee as of January 1st, 2022. IEEE IFS TC is responsible for promoting activities the board technical areas of information forensics and security.
25 november 2021
Mauro Conti elevated to IEEE Fellow
Recognizing his achievements the IEEE Fellow Committee has elevated Mauro Conti to IEEE Fellow with the following citation: - for contributions to communications network security
24 november 2021
Hand Me Your PIN! Inferring ATM PINs of Users Typing with a Covered Hand
Dr. Stjepan Picek, Prof. Mauro Conti, and their colleagues from the University of Padova published a work where they investigated the security of the PIN mechanism for ATMs. They showed that even if a user covers the typing hand with the other hand, a deep learning-based attack can infer the correct PIN.