37 citations · 131 across the 23 of their papers we have counts for
9 papers · 1 filter
Outsourcing Private Machine Learning via Lightweight Secure Arithmetic Computation
Siddharth Garg, Zahra Ghodsi, Carmit Hazay +3
In several settings of practical interest, two parties seek to collaboratively perform inference on their private data using a public machine learning model. For instance, several…
TrojanZero: Switching Activity-Aware Design of Undetectable Hardware Trojans with Zero Power and Area Footprint
Imran Hafeez Abbassi, Faiq Khalid, Semeen Rehman +4
Conventional Hardware Trojan (HT) detection techniques are based on the validation of integrated circuits to determine changes in their functionality, and on non-invasive side-chan…
Matching Graphs with Community Structure: A Concentration of Measure Approach
F. Shirani, S. Garg, E. Erkip
In this paper, matching pairs of random graphs under the community structure model is considered. The problem emerges naturally in various applications such as privacy, image proce…
FATE: Fast and Accurate Timing Error Prediction Framework for Low Power DNN Accelerator Design
Jeff Zhang, Siddharth Garg
Deep neural networks (DNN) are increasingly being accelerated on application-specific hardware such as the Google TPU designed especially for deep learning. Timing speculation is a…
Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks
Kang Liu, Brendan Dolan-Gavitt, Siddharth Garg
Deep neural networks (DNNs) provide excellent performance across a wide range of classification tasks, but their training requires high computational resources and is often outsour…
ThUnderVolt: Enabling Aggressive Voltage Underscaling and Timing Error Resilience for Energy Efficient Deep Neural Network Accelerators
Jeff Zhang, Kartheek Rangineni, Zahra Ghodsi +1
Hardware accelerators are being increasingly deployed to boost the performance and energy efficiency of deep neural network (DNN) inference. In this paper we propose Thundervolt, a…