98 citations · 324 across the 24 of their papers we have counts for
6 papers · 1 filter
Defending Against Model Stealing Attacks with Adaptive Misinformation
Sanjay Kariyappa, Moinuddin K Qureshi
Deep Neural Networks (DNNs) are susceptible to model stealing attacks, which allows a data-limited adversary with no knowledge of the training dataset to clone the functionality of…
TicToc: Enabling Bandwidth-Efficient DRAM Caching for both Hits and Misses in Hybrid Memory Systems
Vinson Young, Zeshan Chishti, Moinuddin K. Qureshi
This paper investigates bandwidth-efficient DRAM caching for hybrid DRAM + 3D-XPoint memories. 3D-XPoint is becoming a viable alternative to DRAM as it enables high-capacity and no…
To Update or Not To Update?: Bandwidth-Efficient Intelligent Replacement Policies for DRAM Caches
Vinson Young, Moinuddin K. Qureshi
This paper investigates intelligent replacement policies for improving the hit-rate of gigascale DRAM caches. Cache replacement policies are commonly used to improve the hit-rate o…
Lookout for Zombies: Mitigating Flush+Reload Attack on Shared Caches by Monitoring Invalidated Lines
Gururaj Saileshwar, Moinuddin K. Qureshi
OS-based page sharing is a commonly used optimization in modern systems to reduce memory footprint. Unfortunately, such sharing can cause Flush+Reload cache attacks, whereby a spy…
A Case for Superconducting Accelerators
Swamit S. Tannu, Poulami Das, Michael L. Lewis +3
As the scaling of conventional CMOS-based technologies slows down, there is growing interest in alternative technologies that can improve performance or energy-efficiency. Supercon…
Improving Adversarial Robustness of Ensembles with Diversity Training
Sanjay Kariyappa, Moinuddin K. Qureshi
Deep Neural Networks are vulnerable to adversarial attacks even in settings where the attacker has no direct access to the model being attacked. Such attacks usually rely on the pr…