1 code implementation • 12 Jul 2021 • Soham Pal, Yash Gupta, Aditya Kanade, Shirish Shevade
Machine-Learning-as-a-Service providers expose machine learning (ML) models through application programming interfaces (APIs) to developers.
1 code implementation • 7 Feb 2020 • Soham Pal, Yash Gupta, Aditya Shukla, Aditya Kanade, Shirish Shevade, Vinod Ganapathy
We demonstrate that (1) it is possible to use ACTIVETHIEF to extract deep classifiers trained on a variety of datasets from image and text domains, while querying the model with as few as 10-30% of samples from public datasets, (2) the resulting model exhibits a higher transferability success rate of adversarial examples than prior work, and (3) the attack evades detection by the state-of-the-art model extraction detection method, PRADA.
no code implementations • 22 May 2019 • Soham Pal, Yash Gupta, Aditya Shukla, Aditya Kanade, Shirish Shevade, Vinod Ganapathy
Machine learning models trained on confidential datasets are increasingly being deployed for profit.
1 code implementation • 4 Feb 2017 • Rahul Gupta, Soham Pal, Aditya Kanade, Shirish Shevade
The problem of automatically fixing programming errors is a very active research topic in software engineering.