34 citations · 49 across the 4 of their papers we have counts for
4 papers · 1 filter
Taming Data Challenges in ML-based Security Tasks Using Generative AI
Shravya Kanchi, Neal Mangaokar, Aravind Cheruvu +4
Machine learning-based supervised classifiers are widely used for security tasks, and their improvement has been largely focused on algorithmic advancements. We argue that data cha…
Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models
Neal Mangaokar, Jiameng Pu, Parantapa Bhattacharya +2
Advances in deep neural networks (DNNs) have shown tremendous promise in the medical domain. However, the deep learning tools that are helping the domain, can also be used against…
T-Miner: A Generative Approach to Defend Against Trojan Attacks on DNN-based Text Classification
Ahmadreza Azizi, Ibrahim Asadullah Tahmid, Asim Waheed +5
Deep Neural Network (DNN) classifiers are known to be vulnerable to Trojan or backdoor attacks, where the classifier is manipulated such that it misclassifies any input containing…
Deepfake Videos in the Wild: Analysis and Detection
Jiameng Pu, Neal Mangaokar, Lauren Kelly +5
AI-manipulated videos, commonly known as deepfakes, are an emerging problem. Recently, researchers in academia and industry have contributed several (self-created) benchmark deepfa…