Dr. Gergely Ács

Assistant Professor

acs (at) crysys.hu

web: www.crysys.hu/~acs/
publications: MTMT
office: I.E. 430
tel: +36 1 463 2047
fax: +36 1 463 3263

Short Bio

Gergely ÁCS gergej ɑ:tʃ received the M.Sc. and Ph.D. degree in Computer Science from the Budapest University of Technology and Economics (BME), where he conducted research in the Laboratory of Cryptography and System Security (CrySyS). Currently, he is an assistant professor at Budapest University of Technology and Economics (BME), in Hungary. Before that, he was a post-doc and then research engineer in Privatics Team at INRIA, in France. His general research interests include data privacy and security.

Current Courses

IT Security (VIHIAC01)

This BSc course gives an overview of the different areas of IT security with the aim of increasing the security awareness of computer science students and shaping their attitude towards designing and using secure computing systems. The course prepares BSc students for security challenges that they may encounter during their professional carrier, and at the same time, it provides a basis for those students who want to continue their studies at MSc level (taking, for instance, our IT Security minor specialization). We put special emphasis on software security and the practical aspects of developing secure programs.

IT Security (in English) (VIHIAC01)

This BSc course gives an overview of the different areas of IT security with the aim of increasing the security awareness of computer science students and shaping their attitude towards designing and using secure computing systems. The course prepares BSc students for security challenges that they may encounter during their professional carrier, and at the same time, it provides a basis for those students who want to continue their studies at MSc level (taking, for instance, our IT Security minor specialization). We put special emphasis on software security and the practical aspects of developing secure programs.

Privacy-Preserving Technologies (VIHIAV35)

The sharing and explotation of the ever-growing data about individuals raise serious privacy concerns these days. Is it possible to derive (socially or individually) useful information about people from this Big Data without revealing personal information?
This course provides a detailed overview of data privacy. It focuses on different privacy problems of web tracking, data sharing, and machine learning, as well as their mitigation techniques. The aim is to give the essential (technical) background knowledge needed to identify and protect personal data. These skills are becoming a must of every data/software engineer and data protection officer dealing with personal and sensitive data, and are also required by the upcoming European General Data Protection Regulation (GDPR).

Student Project Proposals

Személyes adatok visszafejtése

Számos cég/szervezet/kormány oszt meg egymással adatokat, amelyek vagy "anonimizáltak" vagy aggregált (statisztikai) adatok. Sajnos az adatok megfelelő anonimizációja nehéz, és gyakran anonimnak vélt adatokból konkrét személyek adatai visszafejthetők [1] [2]. Hasonlóan, aggregált adatokból is visszafejthetők személyes adatok, ha túl sok aggregált adatot adunk ki, vagy az adat jellege lehetővé teszi konkrét személyek adatainak visszafejtését [3] A kérdés gyakorlati fontosságát a közelgő általános európai adatvédelmi rendelet (GDPR) adja, ami előírja az adatok megfelelő anonimizációját.

Érzékeny adatok inferenciája

Napjainkban sok felhasználó osztja meg a személyes adatát harmadik féllel (cég/kormány/szervezetek), anélkül, hogy tudnák érzékeny adatot osztanak meg. Honnan tudná valaki, hogy a saját áramfogyasztásából kitalálható a vallása, vagy a lakóhelyéből esetleg a pénzügyi helyzete esetleg rassza? Az ilyen "rejtett" információk felfedése diszkriminációra adhat okot.