111 citations · 151 across the 5 of their papers we have counts for
6 papers
InferNet: Exploiting Aggregate GPU Profiles as Side-Channel for DNN Architecture Inference
Raja Hasnain Anwar, Jonah O'Brien Weiss, Tiago Alves +1
Deep Neural Networks (DNNs) have become ubiquitous for their ability to solve problems across various domains, including computer vision, natural language processing, and speech re…
Measuring Progress on Scalable Oversight for Large Language Models
Samuel R. Bowman, Jeeyoon Hyun, Ethan Perez +43
Developing safe and useful general-purpose AI systems will require us to make progress on scalable oversight: the problem of supervising systems that potentially outperform us on m…
Hardening DNNs against Transfer Attacks during Network Compression using Greedy Adversarial Pruning
Jonah O'Brien Weiss, Tiago Alves, Sandip Kundu
The prevalence and success of Deep Neural Network (DNN) applications in recent years have motivated research on DNN compression, such as pruning and quantization. These techniques…
MILR: Mathematically Induced Layer Recovery for Plaintext Space Error Correction of CNNs
Jonathan Ponader, Sandip Kundu, Yan Solihin
The increased use of Convolutional Neural Networks (CNN) in mission critical systems has increased the need for robust and resilient networks in the face of both naturally occurrin…
Deep-Lock: Secure Authorization for Deep Neural Networks
Manaar Alam, Sayandeep Saha, Debdeep Mukhopadhyay +1
Trained Deep Neural Network (DNN) models are considered valuable Intellectual Properties (IP) in several business models. Prevention of IP theft and unauthorized usage of such DNN…
Physical Design Obfuscation of Hardware: A Comprehensive Investigation of Device- and Logic-Level Techniques
Arunkumar Vijayakumar, Vinay C. Patil, Daniel E. Holcomb +2
The threat of hardware reverse engineering is a growing concern for a large number of applications. A main defense strategy against reverse engineering is hardware obfuscation. In…