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.
Severin Perez, Masters Student, School of Information, UC Berkeley
Artificial intelligence (AI) is a field that promises to fundamentally change human society. Researchers, policymakers, and practitioners largely agree that AI could provide immense benefit to humanity; however, it also poses significant risks. As we speed towards the former, we may inadvertently and irrevocably be committing ourselves to the latter....
Sarah Barrington, Masters Student, School of Information, UC Berkeley
Online abuse is becoming an increasingly prevalent issue in modern day society, with 41% of Americans having experienced online harassment in some capacity in 2021. People who identify as women, in particular, can be subjected to a wide range of abusive behavior online, with gender-specific experiences cited broadly in recent...
Jacky Ho, Graduate Student, School of Information, UC Berkeley David Ng, Graduate Student, School of Information, UC Berkeley Atefeh Namvaryshad, Graduate Student, School of Information, UC Berkeley Calvin Szeto, Graduate Student, School of Information, UC Berkeley Jack Glasgow, Graduate Student, School of Information, UC Berkeley Kumud Kalia, Graduate Student, School of Information, UC Berkeley
For many years, we have heard about the shortage of cybersecurity professionals. Despite there being many opportunities to study and work in the cybersecurity space, students are reluctant to pursue further studies or a career in cybersecurity. The perception of cybersecurity as a purely technical domain has put them off...
Ji Su Yoo, PhD Student, School of Information, UC Berkeley
Misinformation and disinformation campaigns often rely on bots and fake accounts to impersonate human users with similar demographic characteristics, political beliefs, and social values as their audience to establish credibility. Such nefarious efforts are successful because human beliefs and behaviors about new information are based on the identity of the...
Current machine learning models suffer from evasion attacks such as adversarial examples. This introduces security and safety concerns that lack any clear solution. Recently, the usage of random transformations has emerged as a promising defense against the attack. Here, we hope to extend this general idea to build a defense...
We aim to build neural networks that are intrinsically robust against adversarial attacks. We focus on classifying images in real-world scenarios with complex backgrounds under unforeseen adversarial attacks. Previous defenses lack interpretability and have limited robustness against unforeseen attacks, failing to deliver trustworthiness to users. We will study Bayesian models,...
Nikita Samarin, PhD Student, EECS, UC Berkeley Moses Namara, PhD Student, Clemson University Joanne Ma, Graduate Student, School of Information, UC Berkeley Aparna (Abby) Krishnan, Undergraduate Student, University of Texas at Austin
Recent events have placed a renewed focus on the issue of racial justice in the United States and other countries. One dimension of this issue that has received considerable attention is the security and privacy threats and vulnerabilities faced by communities of color. This project aims to combine insights about...
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 United States lacks a comprehensive federal privacy regulation and instead relies on industry-specific or state-specific discrete privacy laws. On the state level, the California Consumer Privacy Act (CCPA)—which came into effect on January 1, 2020, and became enforceable on July 1, 2020— was enacted to provide enhanced privacy protections...
Noura Alomar, PhD Student, International Computer Science Institute, UC Berkeley Primal Wijesekera, Staff Research Scientist, International Computer Science Institute, UC Berkeley
Security vulnerabilities pose a grave danger to the integrity of any system because they can undermine almost any protection mechanism organizations put in place to defend themselves against potential attacks. As such, finding vulnerabilities before the software gets deployed or after putting software in production is a critical task in...
Computer vision has been integrated into many areas of our lives, including facial recognition, augmented reality, autonomous driving, and healthcare. However, making them more accurate and generalizing to real world data alone is no longer sufficient, we have to safe-guard their robustness against malicious attacks in cyberspace. Compared with the...