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Deadlines for International Cooperation in AI

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....

Gamification of Cybersecurity Education

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...

Misinformation Corrections

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...

Robust Machine Learning via Random Transformation

Chawin Sitawarin, PhD Student, EECS, UC Berkeley
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...

Towards Bayesian Classifiers that are Robust Against Adversarial Attacks

An Ju, PhD Student, EECS, UC Berkeley
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,...

Examining the Landscape of Digital Security and Privacy Assistance for Racial Minority Groups

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...

Investigating the Compliance of Android App Developers with the California Consumer Privacy Act (CCPA)

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...

A Comprehensive Investigation of Developers’ Remediation Practices

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...

Reverse Engineer and Counter Adversarial Attacks with Unsupervised Representation Learning

Xudong Wang, PhD Student, EECS, UC Berkeley
Nils Worzyk, Postdoctoral Researcher, EECS, UC Berkeley
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...
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