133 citations · 251 across the 26 of their papers we have counts for
8 papers · 1 filter
Data Leakage via Access Patterns of Sparse Features in Deep Learning-based Recommendation Systems
Hanieh Hashemi, Wenjie Xiong, Liu Ke +4
Online personalized recommendation services are generally hosted in the cloud where users query the cloud-based model to receive recommended input such as merchandise of interest o…
DisaggRec: Architecting Disaggregated Systems for Large-Scale Personalized Recommendation
Liu Ke, Xuan Zhang, Benjamin Lee +2
Deep learning-based personalized recommendation systems are widely used for online user-facing services in production datacenters, where a large amount of hardware resources are pr…
Efficient Privacy-Preserving Machine Learning with Lightweight Trusted Hardware
Pengzhi Huang, Thang Hoang, Yueying Li +2
In this paper, we propose a new secure machine learning inference platform assisted by a small dedicated security processor, which will be easier to protect and deploy compared to…
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning using Independent Component Analysis
Sanjay Kariyappa, Chuan Guo, Kiwan Maeng +4
Federated learning (FL) aims to perform privacy-preserving machine learning on distributed data held by multiple data owners. To this end, FL requires the data owners to perform tr…
AutoCAT: Reinforcement Learning for Automated Exploration of Cache-Timing Attacks
Mulong Luo, Wenjie Xiong, Geunbae Lee +6
The aggressive performance optimizations in modern microprocessors can result in security vulnerabilities. For example, timing-based attacks in processor caches can steal secret ke…
Accelerating Path Planning for Autonomous Driving with Hardware-Assisted Memoization
Mulong Luo, G. Edward Suh
Path planning for autonomous driving with dynamic obstacles poses a challenge because it needs to perform a higher-dimensional search (with time-dimension) while still meeting real…
Verifiable Access Control for Augmented Reality Localization and Mapping
Shaowei Zhu, Hyo Jin Kim, Maurizio Monge +4
Localization and mapping is a key technology for bridging the virtual and physical worlds in augmented reality (AR). Localization and mapping works by creating and querying maps ma…
Structured Pruning is All You Need for Pruning CNNs at Initialization
Yaohui Cai, Weizhe Hua, Hongzheng Chen +3
Pruning is a popular technique for reducing the model size and computational cost of convolutional neural networks (CNNs). However, a slow retraining or fine-tuning procedure is of…