no code implementations • 24 Oct 2023 • Valentin Hartmann, Anshuman Suri, Vincent Bindschaedler, David Evans, Shruti Tople, Robert West
A major part of this success is due to their huge training datasets and the unprecedented number of model parameters, which allow them to memorize large amounts of information contained in the training data.
no code implementations • 13 May 2022 • Wenxuan Bao, Luke A. Bauer, Vincent Bindschaedler
The use of differentially private learning algorithms in a "drop-in" fashion -- without accounting for the impact of differential privacy (DP) noise when choosing what feature engineering operations to use, what features to select, or what neural network architecture to use -- yields overly complex and poorly performing models.
no code implementations • 10 Mar 2022 • Hadi Abdullah, Aditya Karlekar, Saurabh Prasad, Muhammad Sajidur Rahman, Logan Blue, Luke A. Bauer, Vincent Bindschaedler, Patrick Traynor
We begin by comparing 20 recent attack papers, classifying and measuring their suitability to serve as the basis of new "robust to transcription" but "easy for humans to understand" CAPTCHAs.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
1 code implementation • 18 Nov 2021 • Jiayuan Ye, Aadyaa Maddi, Sasi Kumar Murakonda, Vincent Bindschaedler, Reza Shokri
Membership inference attacks are used as an auditing tool to quantify this leakage.
no code implementations • 13 Oct 2021 • Luke A. Bauer, James K. Howes IV, Sam A. Markelon, Vincent Bindschaedler, Thomas Shrimpton
We introduce a new type of format-transforming encryption where the format of ciphertexts is implicitly encoded within a machine-learned generative model.
no code implementations • ICLR 2022 • Hadi Abdullah, Aditya Karlekar, Vincent Bindschaedler, Patrick Traynor
The targeted transferability of adversarial samples enables attackers to exploit black-box models in the real-world.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 13 Jul 2020 • Hadi Abdullah, Kevin Warren, Vincent Bindschaedler, Nicolas Papernot, Patrick Traynor
Like other systems based on neural networks, recent research has demonstrated that speech and speaker recognition systems are vulnerable to attacks using manipulated inputs.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
1 code implementation • 13 Feb 2018 • Yunhui Long, Vincent Bindschaedler, Lei Wang, Diyue Bu, Xiao-Feng Wang, Haixu Tang, Carl A. Gunter, Kai Chen
Membership Inference Attack (MIA) determines the presence of a record in a machine learning model's training data by querying the model.
no code implementations • 26 Aug 2017 • Vincent Bindschaedler, Reza Shokri, Carl A. Gunter
We demonstrate the efficiency of this generative technique on a large dataset; it is shown to preserve the utility of original data with respect to various statistical analysis and machine learning measures.