However, the issue of adversarial robustness of models for code has gone largely unnoticed. In this work, we explore this issue by: (i) instantiating adversarial attacks for code (a domain with discrete and highly structured inputs), (ii) showing that, similar to other domains, neural models...
Paper Add Code Adaptive Batch Normalization Networks for Adversarial Robustness no code yet • 20 May 2024 In this paper, we aim at a non-AT defense: How to design a defense method that gets rid of AT but is still robust against strong adversarial attacks? Paper Add Code Causal...
Code Issues Pull requests Discussions Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams python machine-learning privacy ai attack extraction inference artificial-intelligence evasion red-team poisoning adver...
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To sum up, we have two options of pretrained models to use for transfer learning. We can either use standard models that have high accuracy but little robustness on the source task; or we can use adversarially robust models, which are worse in terms of ImageNet accuracy but are robust and...
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To the best of our knowledge, ROBY is the first light-weighted attack-independent robustness evaluation metric general to a wide range of deep models. The code of it can be downloaded at https://github.com/Allen-piexl/ROBY. Introduction In recent years, deep learning(DL) has solved a ...
Pin-Yu Chen, Cho-Jui Hsieh, in Adversarial Robustness for Machine Learning, 2023 1.1 What is adversarial machine learning? Adversarial machine learning (AdvML) refers to the methodology of introducing a virtual adversary for evaluating and improving the performance of a machine learning (ML) system...
advertorch is a toolbox for adversarial robustness research. It contains various implementations for attacks, defenses and robust training methods. advertorch is built on PyTorch (Paszke et al., 2017), and leverages the advantages of the dynamic computational graph to provide concise and efficient ref...
(56%)Daomin Ji; Hui Luo; Zhifeng Bao; Shane Culpepper On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code. (38%)Md Imran Hossen; Xiali Hei Parallel Stacked Aggregated Network for Voice Authentication in IoT-Enabled Smart Devices. (10%)Awais Khan; Ijaz Ul Haq; ...