10 citations · 11 across the 2 of their papers we have counts for
4 papers
Unlocking Visual Secrets: Inverting Features with Diffusion Priors for Image Reconstruction
Sai Qian Zhang, Ziyun Li, Chuan Guo +5
Inverting visual representations within deep neural networks (DNNs) presents a challenging and important problem in the field of security and privacy for deep learning. The main go…
Analysis and Mitigations of Reverse Engineering Attacks on Local Feature Descriptors
Deeksha Dangwal, Vincent T. Lee, Hyo Jin Kim +9
As autonomous driving and augmented reality evolve, a practical concern is data privacy. In particular, these applications rely on localization based on user images. The widely ado…
SoK: Opportunities for Software-Hardware-Security Codesign for Next Generation Secure Computing
Deeksha Dangwal, Meghan Cowan, Armin Alaghi +3
Users are demanding increased data security. As a result, security is rapidly becoming a first-order design constraint in next generation computing systems. Researchers and practit…
Porcupine: A Synthesizing Compiler for Vectorized Homomorphic Encryption
Meghan Cowan, Deeksha Dangwal, Armin Alaghi +3
Homomorphic encryption (HE) is a privacy-preserving technique that enables computation directly on encrypted data. Despite its promise, HE has seen limited use due to performance o…