Grant is a second-year Ph.D. student at UC Berkeley, advised by Vern Paxson and David Wagner. His work explores how the security community can leverage empirical studies and data analysis to build secure systems and craft effective human/policy-oriented mitigations against attackers. Previously, he received his bachelors in computer science and graduated with honors from Stanford University.
Over the past few years, attackers have routinely used social engineering attacks to infect millions of users’ machines and penetrate a myriad of enterprise and government systems. While prior work has developed many defenses against cyber-attacks that exploit code vulnerabilities, social engineering attacks require a different class of defenses and remain an open problem. Whereas traditional attacks target technical weaknesses in machines and programs, social engineering attacks involve a fundamentally different kind of interaction: exploiting human trust in order to trick users into performing a malicious action. Through large-scale data analysis of digital communication patterns, Grant’s research aims to construct systems that can reason about online human interactions and prevent attempts to abuse and manipulate a user’s trust. His current work focuses on using this approach to defend against spear phishing attacks.