1 citations · 2 across the 7 of their papers we have counts for
10 papers · 1 filter
Efficient Storage Integrity in Adversarial Settings
Quinn Burke, Ryan Sheatsley, Yohan Beugin +4
Storage integrity is essential to systems and applications that use untrusted storage (e.g., public clouds, end-user devices). However, known methods for achieving storage integrit…
Adversarial Agents: Black-Box Evasion Attacks with Reinforcement Learning
Kyle Domico, Jean-Charles Noirot Ferrand, Ryan Sheatsley +3
Attacks on machine learning models have been extensively studied through stateless optimization. In this paper, we demonstrate how a reinforcement learning (RL) agent can learn a n…
Targeting Alignment: Extracting Safety Classifiers of Aligned LLMs
Jean-Charles Noirot Ferrand, Yohan Beugin, Eric Pauley +2
Alignment in large language models (LLMs) is used to enforce guidelines such as safety. Yet, alignment fails in the face of jailbreak attacks that modify inputs to induce unsafe ou…
ParTEETor: A System for Partial Deployments of TEEs within Tor
Rachel King, Quinn Burke, Yohan Beugin +5
The Tor anonymity network allows users such as political activists and those under repressive governments to protect their privacy when communicating over the internet. At the same…
Characterizing the Modification Space of Signature IDS Rules
Ryan Guide, Eric Pauley, Yohan Beugin +2
Signature-based Intrusion Detection Systems (SIDSs) are traditionally used to detect malicious activity in networks. A notable example of such a system is Snort, which compares net…
Systematic Evaluation of Geolocation Privacy Mechanisms
Alban Héon, Ryan Sheatsley, Quinn Burke +4
Location data privacy has become a serious concern for users as Location Based Services (LBSs) have become an important part of their life. It is possible for malicious parties hav…