44 citations · 94 across the 12 of their papers we have counts for
6 papers · 1 filter
AI Agents Enable Adaptive Computer Worms
Jonas Guan, Tom Blanchard, Hanna Foerster +3
A computer worm is malware that spreads on a network by replicating itself from one machine to another. Traditional worms, like WannaCry, exploited predetermined vulnerabilities, a…
The Erasure Illusion: Stress-Testing the Generalization of LLM Forgetting Evaluation
Hengrui Jia, Taoran Li, Jonas Guan +1
Machine unlearning aims to remove specific data influences from trained models, a capability essential for adhering to copyright laws and ensuring AI safety. Current unlearning met…
Backdoor Detection through Replicated Execution of Outsourced Training
Hengrui Jia, Sierra Wyllie, Akram Bin Sediq +2
It is common practice to outsource the training of machine learning models to cloud providers. Clients who do so gain from the cloud's economies of scale, but implicitly assume tru…
SoK: Machine Learning Governance
Varun Chandrasekaran, Hengrui Jia, Anvith Thudi +3
The application of machine learning (ML) in computer systems introduces not only many benefits but also risks to society. In this paper, we develop the concept of ML governance to…
Entangled Watermarks as a Defense against Model Extraction
Hengrui Jia, Christopher A. Choquette-Choo, Varun Chandrasekaran +1
Machine learning involves expensive data collection and training procedures. Model owners may be concerned that valuable intellectual property can be leaked if adversaries mount mo…
Machine Unlearning
Lucas Bourtoule, Varun Chandrasekaran, Christopher A. Choquette-Choo +5
Once users have shared their data online, it is generally difficult for them to revoke access and ask for the data to be deleted. Machine learning (ML) exacerbates this problem bec…