Towards privacy aware deep learning for embedded systems

Author:

Duddu Vasisht1,Boutet Antoine1,Shejwalkar Virat2

Affiliation:

1. Univ Lyon, Inria

2. University of Massachusetts Amherst

Publisher

ACM

Reference39 articles.

1. Martin Abadi Andy Chu Ian Goodfellow H. Brendan McMahan Ilya Mironov Kunal Talwar and Li Zhang. 2016. Deep Learning with Differential Privacy. In CCS. 308--318. Martin Abadi Andy Chu Ian Goodfellow H. Brendan McMahan Ilya Mironov Kunal Talwar and Li Zhang. 2016. Deep Learning with Differential Privacy. In CCS. 308--318.

2. Alfredo Canziani , Adam Paszke , and Eugenio Culurciello . 2016. An Analysis of Deep Neural Network Models for Practical Applications. (05 2016 ). Alfredo Canziani, Adam Paszke, and Eugenio Culurciello. 2016. An Analysis of Deep Neural Network Models for Practical Applications. (05 2016).

3. Nicholas Carlini Chang Liu Úlfar Erlingsson Jernej Kos and Dawn Song. 2019. The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks. In USENIX Security. 267--284. Nicholas Carlini Chang Liu Úlfar Erlingsson Jernej Kos and Dawn Song. 2019. The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks. In USENIX Security. 267--284.

4. Andrea Cavallaro Mohammad Malekzadeh and Ali Shahin Shamsabadi. 2020. Deep Learning for Privacy in Multimedia. In MM. 4777--4778. Andrea Cavallaro Mohammad Malekzadeh and Ali Shahin Shamsabadi. 2020. Deep Learning for Privacy in Multimedia. In MM. 4777--4778.

5. Jasmine Collins Jascha Sohl-Dickstein and David Sussillo. 2017. Capacity and Trainability in Recurrent Neural Networks. arXiv:1611.09913 [stat.ML] Jasmine Collins Jascha Sohl-Dickstein and David Sussillo. 2017. Capacity and Trainability in Recurrent Neural Networks. arXiv:1611.09913 [stat.ML]

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