Privacy and Security
Privacy and security research are intertwined. Privacy research is the field of research that addresses questions about what information can be inferred about participants (users, devices, etc.) in a computational system and the potential mismatch between such inferences and what the participants expect, what are the underlying ethics questions, and even what is the legal framework. Security research is the field of research that is concerned with questions about how to ensure computational systems provide guarantees such as confidentiality, integrity, availability, etc. of stored and transmitted information. Cryptography is one, but not the only, component of a security system. Combined, privacy and security research aspire to design and develop technologies to protect information, systems, and individuals from various cyber threats and privacy infringements. The sub-categories of privacy and security research on which the team is working are:
- Privacy in Machine Learning, (Omid, Bailey, Nidhi, Euijin)
- Differential Privacy, (Nidhi)
- Multiparty Computation, (Bailey)
- Homomorphic Encryption, (Omid, Euijin)
- Usable Privacy, (Bailey)
- Federated Learning, (Omid, Bailey, Nidhi, Euijin)
- Law and Policy (Bailey, Nidhi)
- AI/ML for Cyber Security, (Euijin)
- Anomaly Detection, Security Analytics, (Euijin)
- Adversarial Attacks, (Omid, Euijin)
- Network Security, ( Yannis, Euijin)
- Web Security, (Euijin)
- Resilience and Robustness of Systems (Nidhi, Euijin),
- Fraud Detection, (Euijin)
- Cyber-physical System Security, ( Yannis, Omid)
- Mobile and IoT Security ( Yannis, Omid, Euijin)