Course Contents:
This course provides a multidisciplinary perspective on privacy, looking in depth at the foundations of privacy, privacy issues and challenges in emerging technologies, concepts for privacy engineering in software/systems, and usable privacy.
In this seminar, we will discuss the privacy implications of emerging technologies, focusing on environments where new privacy definitions and enforcement mechanisms are being developed. More specifically, we will discuss new threats, different attack techniques, ways to defend against them, and techniques for evaluating the usability of privacy solutions. We will cover new areas such as privacy in/for large language models, de-anonymisation attacks on the metaverse, privacy threat modelling and privacy engineering (how to build privacy into the software development lifecycle?), data anonymisation and distributed machine learning, explainable machine learning; - as well as other areas where concerns have led to significant research. Examples of the latter include privacy in IoT / smart cars, privacy in mobile and social networks.
A strong emphasis will be placed on improving students' ability to conduct scientific research, prepare and deliver a seminar presentation, and submit a written report. Participants will be given a topic and a short list of recent research papers on the given topic. They will be expected to conduct a literature review on the assigned topic, prepare a presentation similar to that required at a scientific conference, and lead/participate in scientific discussions.
During this seminar, students and teachers will simulate the different phases of scientific conferences: Submission of work, peer review, notification/feedback, submission of the final version of the report, presentation and possibly chairing a session.
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- Dozent*in: Hervais Clemence Simo Fhom