Por Xiaojie Zhu (King Abdullah University of Science and Technology).
Privacy-enhancing technologies (PETs) provide a crucial opportunity to harness the power of data while safeguarding data privacy. In this talk, I will first introduce searchable encryption and explore its applications in location-based services and genome data-oriented services. I will then explore how large language models (LLMs) are being applied in password cracking, and discuss the importance of preserving data deletion rights and the strategies to achieve this in federated learning. Lastly, I will present my ongoing cooperation project with LASIGE about adversarial machine learning in intrusion detection systems (IDS).
Short Bio: Xiaojie Zhu is a research scientist at KAUST. Previously, he served as an Assistant Professor of Cybersecurity at Abu Dhabi University and worked as a lead cryptography/software engineer at the Technology Innovation Institute, UAE. He earned his PhD from the University of Oslo, Norway, in 2021. His main research interests include data security and privacy, applied cryptography, and AI for cybersecurity.
Xiajie Zhu’s research falls within the scope of the DS2, DSI, and CPS research lines.
