7 matches found
Jailbreaking Open-Weight LLMs Via Random Embedding Perturbations
While open-weight models have enjoyed steady progress in capabilities and wide adoption across multiple domains, their safety remains an important concern. One key feature is the ability to refuse or deflect harmful, malicious, or insensitive prompts. In this paper, we expose safety vulnerabiliti...
Traffic-Aware Randomized Smoothing for LLM-Based Network Intrusion Detection
Large language model LLM-based intrusion detection systems IDS are increasingly studied for security monitoring, yet their robustness against feasible traffic manipulation remains largely empirical. We present Traffic-Aware Randomized Smoothing TA-RS, a classifier-agnostic certified defense that...
Who'S the Evil Twin? Differential Auditing for Undesired Behavior
Detecting hidden behaviors in neural networks poses a significant challenge due to minimal prior knowledge and potential adversarial obfuscation. We explore this problem by framing detection as an adversarial game between two teams: the red team trains two similar models, one trained solely on...
GaussMarker: Robust Dual-Domain Watermark for Diffusion Models
As Diffusion Models DM generate increasingly realistic images, related issues such as copyright and misuse have become a growing concern. Watermarking is one of the promising solutions. Existing methods inject the watermark into the single-domain of initial Gaussian noise for generation, which...
PHSafe: Disclosure Avoidance for the 2020 Census Supplemental Demographic and Housing Characteristics File (S-DHC)
This article describes the disclosure avoidance algorithm that the U.S. Census Bureau used to protect the 2020 Census Supplemental Demographic and Housing Characteristics File S-DHC. The tabulations contain statistics of counts of U.S. persons living in certain types of households, including...
SafeTab-P: Disclosure Avoidance for the 2020 Census Detailed Demographic and Housing Characteristics File a (Detailed DHC-A)
This article describes the disclosure avoidance algorithm that the U.S. Census Bureau used to protect the Detailed Demographic and Housing Characteristics File A Detailed DHC-A of the 2020 Census. The tabulations contain statistics counts of demographic characteristics of the entire population of...
DP-SMOTE: Integrating Differential Privacy and Oversampling Technique to Preserve Privacy in Smart Homes
Smart homes represent intelligent environments where interconnected devices gather information, enhancing users living experiences by ensuring comfort, safety, and efficient energy management. To enhance the quality of life, companies in the smart device industry collect user data, including...