34 citations · 82 across the 7 of their papers we have counts for
8 papers
Deepfake Text Detection: Limitations and Opportunities
Jiameng Pu, Zain Sarwar, Sifat Muhammad Abdullah +5
Recent advances in generative models for language have enabled the creation of convincing synthetic text or deepfake text. Prior work has demonstrated the potential for misuse of d…
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…
Embedding Code Contexts for Cryptographic API Suggestion:New Methodologies and Comparisons
Ya Xiao, Salman Ahmed, Wenjia Song +3
Despite recent research efforts, the vision of automatic code generation through API recommendation has not been realized. Accuracy and expressiveness challenges of API recommendat…
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…
Sieve: Actionable Insights from Monitored Metrics in Microservices
Jörg Thalheim, Antonio Rodrigues, Istemi Ekin Akkus +5
Major cloud computing operators provide powerful monitoring tools to understand the current (and prior) state of the distributed systems deployed in their infrastructure. While suc…