5 papers
Differentially Private Spectral Graph Clustering: Balancing Privacy, Accuracy, and Efficiency
Antti Koskela, Mohamed Seif, H. Vincent Poor +1
We study spectral graph clustering under edge differential privacy. We propose a matrix shuffling mechanism that combines randomized edge flipping with a random permutation of the…
Protecting Human Activity Signatures in Compressed IEEE 802.11 CSI Feedback
Mohamed Seif, Atsutse Kludze, Yasaman Ghasempour +3
Explicit channel state information (CSI) feedback in IEEE~802.11 conveys \emph{transmit beamforming directions} by reporting quantized Givens rotation and phase angles that paramet…
Adversary-Aware Private Inference over Wireless Channels
Mohamed Seif, Malcolm Egan, Andrea J. Goldsmith +1
AI-based sensing at wireless edge devices has the potential to significantly enhance Artificial Intelligence (AI) applications, particularly for vision and perception tasks such as…
Detecting Post-generation Edits to Watermarked LLM Outputs via Combinatorial Watermarking
Liyan Xie, Muhammad Siddeek, Mohamed Seif +2
Watermarking has become a key technique for proprietary language models, enabling the distinction between AI-generated and human-written text. However, in many real-world scenarios…
On the Price of Differential Privacy for Spectral Clustering over Stochastic Block Models
Antti Koskela, Mohamed Seif, Andrea J. Goldsmith
We investigate privacy-preserving spectral clustering for community detection within stochastic block models (SBMs). Specifically, we focus on edge differential privacy (DP) and pr…