7 citations · 8 across the 6 of their papers we have counts for
6 papers · 1 filter
Text-Based Personas for Simulating User Privacy Decisions
Kassem Fawaz, Ren Yi, Octavian Suciu +4
The ability to simulate human privacy decisions has significant implications for aligning autonomous agents with individual intent and conducting cost-effective, large-scale privac…
Personalizing Agent Privacy Decisions via Logical Entailment
James Flemings, Ren Yi, Octavian Suciu +3
Personal large language model (LLM) agents increasingly perform tasks that require access to user data, raising concerns about appropriate data disclosure. We show that relying sol…
SNPeek: Side-Channel Analysis for Privacy Applications on Confidential VMs
Ruiyi Zhang, Albert Cheu, Adria Gascon +4
Confidential virtual machines (CVMs) based on trusted execution environments (TEEs) enable new privacy-preserving solutions. Yet, they leave side-channel leakage outside their thre…
Technical Report -- Expected Exploitability: Predicting the Development of Functional Vulnerability Exploits
Octavian Suciu, Connor Nelson, Zhuoer Lyu +2
Assessing the exploitability of software vulnerabilities at the time of disclosure is difficult and error-prone, as features extracted via technical analysis by existing metrics ar…
Technical Report: When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks
Octavian Suciu, Radu Mărginean, Yiğitcan Kaya +2
Recent results suggest that attacks against supervised machine learning systems are quite effective, while defenses are easily bypassed by new attacks. However, the specifications…
Summoning Demons: The Pursuit of Exploitable Bugs in Machine Learning
Rock Stevens, Octavian Suciu, Andrew Ruef +3
Governments and businesses increasingly rely on data analytics and machine learning (ML) for improving their competitive edge in areas such as consumer satisfaction, threat intelli…