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cs.CR2025

MetaSeal: Defending Against Image Attribution Forgery Through Content-Dependent Cryptographic Watermarks

Tong Zhou, Ruyi Ding, Gaowen Liu +5

The rapid growth of digital and AI-generated images has amplified the need for secure and verifiable methods of image attribution. While digital watermarking offers more robust pro…

cs.CR2025

MoEcho: Exploiting Side-Channel Attacks to Compromise User Privacy in Mixture-of-Experts LLMs

Ruyi Ding, Tianhong Xu, Xinyi Shen +2

The transformer architecture has become a cornerstone of modern AI, fueling remarkable progress across applications in natural language processing, computer vision, and multimodal…

cs.CR2025

EXAM: Exploiting Exclusive System-Level Cache in Apple M-Series SoCs for Enhanced Cache Occupancy Attacks

Tianhong Xu, Aidong Adam Ding, Yunsi Fei

Cache occupancy attacks exploit the shared nature of cache hierarchies to infer a victim's activities by monitoring overall cache usage, unlike access-driven cache attacks that foc…

cs.CR2025

MACPruning: Dynamic Operation Pruning to Mitigate Side-Channel DNN Model Extraction

Ruyi Ding, Cheng Gongye, Davis Ranney +2

As deep learning gains popularity, edge IoT devices have seen proliferating deployment of pre-trained Deep Neural Network (DNN) models. These DNNs represent valuable intellectual p…

cs.CR2025

Graph in the Vault: Protecting Edge GNN Inference with Trusted Execution Environment

Ruyi Ding, Tianhong Xu, Aidong Adam Ding +1

Wide deployment of machine learning models on edge devices has rendered the model intellectual property (IP) and data privacy vulnerable. We propose GNNVault, the first secure Grap…