With a focus on malicious software but also covering a broad spectrum of other security applications, students successfully completing the course will be able to build their knowledge and abilities in the following fields:
Developing ML models for malware detection, thus understanding how Antivirus and security solutions work.
Developing strategies to keep an ML model functional over time, thus overcoming challenges such as concept evolution and drift.
Understanding the threats of Adversarial Examples to ML models, thus clarifying the context in which ML solutions are suitable.
Using the emerged Large Language Models (LLMs) to automatically generate code and handle malicious constructions, thus understanding the power of automation.
Using LLMs for security tasks such as bug finding and software repair, thus getting in touch with the multiple possibilities brought by the recent technological developments.
Developing practical skills on deploying adversarial attacks and defenses in third-party (pre-trained) models.