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08/18/2023
Attesting Distributional Properties of Training Data for Machine Learning
The success of machine learning (ML) has been accompanied by increased c...
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04/17/2023
GrOVe: Ownership Verification of Graph Neural Networks using Embeddings
Graph neural networks (GNNs) have emerged as a state-of-the-art approach...
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11/18/2022
Leveraging Algorithmic Fairness to Mitigate Blackbox Attribute Inference Attacks
Machine learning (ML) models have been deployed for high-stakes applicat...
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11/13/2022
Comprehension from Chaos: What Users Understand and Expect from Private Computation
Private computation, which includes techniques like multi-party computat...
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08/21/2022
Inferring Sensitive Attributes from Model Explanations
Model explanations provide transparency into a trained machine learning ...
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02/04/2022
Dikaios: Privacy Auditing of Algorithmic Fairness via Attribute Inference Attacks
Machine learning (ML) models have been deployed for high-stakes applicat...
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12/04/2021
SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for Machine Learning
Data used to train machine learning (ML) models can be sensitive. Member...
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04/26/2021
Good Artists Copy, Great Artists Steal: Model Extraction Attacks Against Image Translation Generative Adversarial Networks
Machine learning models are typically made available to potential client...
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10/02/2020
GECKO: Reconciling Privacy, Accuracy and Efficiency in Embedded Deep Learning
Embedded systems demand on-device processing of data using Neural Networ...
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10/02/2020
Quantifying Privacy Leakage in Graph Embedding
Graph embeddings have been proposed to map graph data to low dimensional...
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10/31/2019
Quantifying (Hyper) Parameter Leakage in Machine Learning
Black Box Machine Learning models leak information about the proprietary...
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10/30/2019
Fault Tolerance of Neural Networks in Adversarial Settings
Artificial Intelligence systems require a through assessment of differen...
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07/06/2019
Adversarial Fault Tolerant Training for Deep Neural Networks
Deep Learning Accelerators are prone to faults which manifest in the for...
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12/31/2018
Stealing Neural Networks via Timing Side Channels
Deep learning is gaining importance in many applications and Cloud infra...
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03/30/2018
