Is AI taking over the world? No, but it's making it less private, Dr. Giuseppe Ateniese

This talk highlights challenges and opportunities for trustworthy AI with a focus on privacy attacks and countermeasures. AI and machine learning have no future if their privacy and security concerns are not addressed. Machine learning models could hide malicious code or backdoors, and leak private information about users. We will explore inference attacks against machine learning models and frameworks (e.g., federated learning), and set out the requirements for privacy-preserving AI systems.

Biography

Dr. Giuseppe Ateniese was with Sapienza-University of Rome (Italy) and Assistant/Associate Professor at Johns Hopkins University (USA), and one of the founders of the JHU Information Security Institute. He was a researcher at IBM Zurich Research lab (Switzerland) and scientist at the Information Sciences Institute of the University of Southern California (USA). He also briefly worked as visiting professor at Microsoft in Redmond (USA). He received the NSF CAREER Award for his research in privacy and security, and the Google Faculty Research Award, the IBM Faculty Award, and the IEEE CISTC Technical Recognition Award for his research on cloud security.

He has contributed to areas such as proxy re-cryptography, anonymous communication, two-party computation, secure storage, and provable data possession. He is currently working on cloud security and machine learning applied to security and intelligence issues for which he received an IBM SUR Award. He is also investigating new security applications for decentralized computing based on the blockchain/bitcoin technology. We look forward to seeing you there for his exciting talk.