CS Other Presentations

Department of Computer Science - University of Cyprus

Besides Colloquiums, the Department of Computer Science at the University of Cyprus also holds Other Presentations (Research Seminars, PhD Defenses, Short Term Courses, Demonstrations, etc.). These presentations are given by scientists who aim to present preliminary results of their research work and/or other technical material. Other Presentations serve as a forum for educating Computer Science students and related announcements are disseminated to the Department of Computer Science (i.e., the csall list):
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Presentations Coordinator: Demetris Zeinalipour

PhD Defense: Hardening Modern Systems and Services for Protecting User Privacy, Mr. Antreas Dionysiou (University of Cyprus, Cyprus), Friday, March 1, 2024, 10:00-11:00 EET.


The Department of Computer Science at the University of Cyprus cordially invites you to the PhD Defense entitled:

Hardening Modern Systems and Services for Protecting User Privacy

Speaker: Mr. Antreas Dionysiou
Affiliation: University of Cyprus, Cyprus
Category: PhD Defense
Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions)
Date: Friday, March 1, 2024
Time: 10:00-11:00 EET
Host: Dr. Georgia Kapitsaki (gkapi-AT-ucy.ac.cy)
URL: https://www.cs.ucy.ac.cy/colloquium/presentations.php?speaker=cs.ucy.pres.2024.dionysiou

Abstract:
In today’s digital landscape, user privacy stands as a fundamental pillar. Safeguarding personal data is not merely a responsibility but a crucial right that bolsters trust, autonomy, and cybersecurity. Upholding privacy nurtures a safe space for innovation and free expression online, contributing to a more ethical digital realm for all. Therefore, modern systems and services must prioritise safeguarding user privacy as a fundamental principle. Given the long history of data breach incidents compromising users’ personal information, even on prestigious web services, one approach in this direction involves hardening password-based authentication. However, instead of solely bolstering the security of these systems, a more pragmatic stance involves transforming them to protect users’ privacy even when fully compromised. This strategy equips web services with an additional layer of security, particularly valuable in adverse scenarios. Nonetheless, users’ privacy can face threats beyond the realm of breaking password-based authentication. For instance, modern systems and services heavily rely on Machine Learning (ML) technologies to perform diverse tasks, including face recognition and medical diagnosis. These systems, if exploited, can significantly jeopardise user privacy. This risk becomes particularly pronounced in scenarios where the training dataset contains sensitive information, such as biomedical records or location traces. Indeed, over the past decade, a substantial body of work has introduced sophisticated attack methodologies exploiting the stochastic nature of ML models. To this end, another promising direction for protecting user privacy involves hardening ML-based systems and services. Developing robust and widely applicable defenses, however, necessitates a thorough understanding and practical evaluation of state-of-the-art attacks targeting ML-based systems. Armed with such knowledge, the scientific community can then devise strategies to defend modern (ML-based) systems and services against contemporary adversaries. In this PhD thesis, we explore both directions. First, within the realm of password-based authentication, we focus on advancing honeyword-based methodologies for timely detecting compromised credentials. Second, concerning ML-based systems and services, our emphasis lies in conducting an extensive feasibility study to assess the practicality and efficacy of contemporary attacks. This comprehensive analysis yields valuable insights crucial for enhancing the overall resilience of these systems.

Short Bio:
Antreas Dionysiou is a Ph.D. candidate at the Department of Computer Science of the University of Cyprus under the supervision of the Associate Professor Elias Athanasopoulos. He is a member of the Security Research in Cyprus (SREC) group. His research interests lie in the area of Secure Authentication, Machine Learning Security, Information Security and Privacy. He holds both B.Sc. and M.Sc. degrees in Computer Science from the University of Cyprus, graduating with first-class honours.

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