4 matches found
Frequency-Domain Mixing Data Augmentation for Malicious Traffic Detection
The strong dynamics of network traffic often force malicious traffic detection models to handle out-of-distribution data. Typically, deep learning-based malicious traffic detection models require a large amount of high-quality training data. However, owing to challenges such as high labeling...
Machine Learning-Based Detection of MCP Attacks
The Model Context Protocol MCP is a new and emerging technology that extends the functionality of large language models, improving workflows but also exposing users to a new attack surface. Several studies have highlighted related security flaws, but MCP attack detection remains underexplored. To...
Sentinel: SOTA Model to Protect against Prompt Injections
Large Language Models LLMs are increasingly powerful but remain vulnerable to prompt injection attacks, where malicious inputs cause the model to deviate from its intended instructions. This paper introduces Sentinel, a novel detection model, qualifire/prompt-injection-sentinel, based on the...
