Bio
Vafa's research focused on leveraging machine learning for end-user security and privacy protection. This was achieved by strengthening the security and privacy defenses over the network stack: in application layer I worked on applying machine learning to build a human-centered anti-fingerprinting defense. In mid-layers I work on the MUD standard for protecting IoT devices through network-microsegmentation., and close to physical layer, I worked on deep learning applications in binary analysis for facilitating reverse engineering of stripped IoT firmware binaries.
Projects
- MUD
- BrowserFingerprintingCountermeasures
- FacilitatingReverseEngineeringoftheIoTfirmware
Recent Publications

Keywords: Security, user interviews, smart home, IoT, 2FA, privacy. [bibtex-entry]
Keywords: IoT, MUD, MUD-Visualizer. [bibtex-entry]
Keywords: IoT, MUD, MUD-Visualizer. [bibtex-entry]