The Center for Long-Term Cybersecurity provides funding to UC Berkeley-affiliated researchers working on a diverse range of security issues, with an emphasis on four priority areas: machine learning and artificial intelligence, building the cyber-talent pipeline, improving cybersecurity governance, and protecting vulnerable online populations. Search below to learn more about our past and current grantees.
Nestor Catano, MICS Student, School of Information, UC Berkeley Yi Zhang, MICS Student, School of Information, UC Berkeley Muhammad Akhtar, MICS Student, School of Information, UC Berkeley
Despite persistent and continuous efforts in the cyber-domain to produce software that is resilient to cybersecurity attacks, software security remains an unmatched challenge as attackers sooner or later find a way to breach adopted security measures. Software supply chain attacks are of particular concern to software security. These attacks seek...
Emma Lurie, PhD Student, School of Information, UC Berkeley
In the United States, people are increasingly turning to online sources to find information about elections. Election information includes everything from mail-in ballot instructions to candidate Facebook page posts. In the U.S., as well as around the world, online misinformation threatens democratic systems. Politicians, technology companies, journalists, and voters all...
Dagin Faulkner, PhD Candidate, City and Regional Planning, UC Berkeley
Smart cities lie at the evolving intersection of people and digital technologies. Establishing cross-sector cybersecurity protocols that treat the smart city as an interdependent assemblage of activities entails more than addressing the costs associated with responding to cyberattacks. This research proposal seeks to answer the question: What are the transaction...
Seyi Olojo, PhD Student, School of Information, UC Berkeley
Our study aims to investigate the social and psychological implications of targeted advertising on individuals with stigmatized health identities. With nearly every user on social media platforms encountering personalized advertising, the personal data economy has become a major component of our everyday lives. This use of personal data, especially as...
Robustness becomes one of the most desired properties in machine learning (ML) models due to their increasing adoption in safety/security-sensitive settings. Most attempts to train robust methods against adversarial manipulation rely on expensive robust optimization and a large amount of data. As a result, they are difficult to scale and...
Lun Wang, PhD Candidate, Department of Electrical Engineering and Computer Science, UC Berkeley Xiaoyuan Liu, PhD Student, Department of Electrical Engineering and Computer Science, UC Berkeley
Privacy regulation compliance is becoming a burden for most companies due to the high cost and inefficiency of human auditing. We propose a regulation enforcement framework, PrivGuard, to reduce the cost and improve productivity by partly replacing human-auditing with a static analyzer. One open challenge is that the static analysis...
James Bartusek, Graduate student, Department of Electrical Engineering and Computer Science, UC Berkeley Abhishek Jain, Associate Professor, Computer Science Department, Johns Hopkins University Guru Vamsi Policharla, Graduate Student, Department of Electrical Engineering and Computer Science, UC Berkeley
As end-to-end encrypted storage and messaging services become widely adopted, law enforcement agencies have increasingly expressed concern that such services interfere with their ability to maintain public safety. Indeed, there is a direct tension between preserving user privacy and enabling content moderation on such platforms. Recent research has begun to...
Nikita Samarin, PhD Student, EECS, UC Berkeley Chris Hoofnagle, Professor of Law in Residence and Adjunct Professor, School of Information, UC Berkeley Jordan Fischer, Professor of Law and Lecturer, School of Information, UC Berkeley and Drexel University School of Law Primal Wijesekera, Staff Research Scientist, International Computer Science Institute, UC Berkeley
The California Consumer Privacy Act (CCPA) provides California residents with a range of enhanced privacy protections and rights. Our project aims to investigate the extent to which Android app developers comply with the provisions of the California Consumer Privacy Act (CCPA) that require them to provide consumers with accurate privacy...
Conor Gilsenan, PhD Student, Department of Electrical Engineering and Computer Science, UC Berkeley
Multi-factor authentication (MFA) — logging in with a combination of at least two of something you know, something you physically have, or something you are — has consistently been shown to drastically increase the security of online accounts compared to the use of a password alone. Though many online services...
Yoon Lee, PhD Candidate, Department of Industrial Engineering and Operations Research, UC Berkeley
A limitation of existing approaches for incentive design in cybersecurity insurance contracts (CIC) is that they do not incorporate fairness. Fairness is crucial for incentives because improper design can harm people of certain classes (e.g., race or gender). In this study, we develop optimization problems for CIC design that incorporate...