Our society is increasingly transitioning towards an information-centric paradigm, enabled by pervasive networked computing devices. This has brought concerns about security and privacy to a forefront; attackers can exploit vulnerabilities in our systems and protocols to compromise our critical infrastructure as well as end-user devices. How can we secure our computing systems? How can we protect the privacy of our sensitive information?
By leveraging our strengths in areas ranging from communication networks and computer architecture to information systems and machine learning, electrical engineering researchers at Princeton are in a unique position to counter security and privacy threats. We are designing secure and trustworthy computing architectures for mobile and wearable devices, medical devices and smart cars. We are creating privacy-preserving and secure protocols for communication between devices, including anonymity systems such as Tor and security mechanisms for Internet routing. We are investigating approaches that protect the privacy of user data, with applications for finance, medical records, social networks and cloud computing. Finally, we are building the mathematical foundations of security and privacy, including information theoretic security, adversarial machine learning, and privacy-utility trade-offs.