Binary similarity analysis determines if two binary executables are from...
Backdoor attacks have emerged as a prominent threat to natural language
...
Reusing off-the-shelf code snippets from online repositories is a common...
Multi-sensor fusion (MSF) is widely adopted for perception in autonomous...
Self-supervised learning in computer vision trains on unlabeled data, su...
Monocular Depth Estimation (MDE) is a critical component in applications...
Most existing methods to detect backdoored machine learning (ML) models ...
Deep Learning backdoor attacks have a threat model similar to traditiona...
We conduct a systematic study of backdoor vulnerabilities in normally tr...
Federated Learning (FL) is a distributed learning paradigm that enables
...
Deep learning has substantially boosted the performance of Monocular Dep...
Pervasive backdoors are triggered by dynamic and pervasive input
perturb...
(Source) Code summarization aims to automatically generate summaries/com...
Code search is a widely used technique by developers during software
dev...
We develop a novel optimization method for NLPbackdoor inversion. We lev...
Backdoor attack injects malicious behavior to models such that inputs
em...
Back-door attack poses a severe threat to deep learning systems. It inje...
We propose a novel technique that can generate natural-looking adversari...
We propose a new type of adversarial attack to Deep Neural Networks (DNN...
A novel and efficient end-to-end learning model for automatic modulation...
Adversarial sample attacks perturb benign inputs to induce DNN misbehavi...