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Found 6 papers, 4 papers with code
LOTUS: Evasive and Resilient Backdoor Attacks through Sub-Partitioning
Backdoor attack poses a significant security threat to Deep Learning applications.
CodeArt: Better Code Models by Attention Regularization When Symbols Are Lacking
Our pre-trained model can improve the SOTAs in these tasks from 53% to 64%, 49% to 60%, and 74% to 94%, respectively.
When Dataflow Analysis Meets Large Language Models
Dataflow analysis is a powerful code analysis technique that reasons dependencies between program values, offering support for code optimization, program comprehension, and bug detection.
Nova$^+$: Generative Language Models for Binaries
We build Nova$^+$ to further boost Nova using two new pre-training tasks, i. e., optimization generation and optimization level prediction, which are designed to learn binary optimization and align equivalent binaries.
Detecting Backdoors in Pre-trained Encoders
We show the effectiveness of our method on image encoders pre-trained on ImageNet and OpenAI's CLIP 400 million image-text pairs.
BEAGLE: Forensics of Deep Learning Backdoor Attack for Better Defense
Attack forensics, a critical counter-measure for traditional cyber attacks, is hence of importance for defending model backdoor attacks.
