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...

A Risk-Stratified Benchmark Dataset for Bad Randomness (SWC-120) Vulnerabilities in Ethereum Smart Contracts

Many Ethereum smart contracts rely on block attributes such as block.timestamp or blockhash to generate random numbers for applications like lotteries and games. However, these values are predictable and miner-manipulable, creating the Bad Randomness vulnerability SWC-120 that has led to real-wor...

Introducing Nylon Face Mask Attacks: A Dataset for Evaluating Generalised Face Presentation Attack Detection

Face recognition systems are increasingly deployed across a wide range of applications, including smartphone authentication, access control, and border security. However, these systems remain vulnerable to presentation attacks PAs, which can significantly compromise their reliability. In this wor...

Decoding Latent Attack Surfaces in LLMs: Prompt Injection Via HTML in Web Summarization

Large Language Models LLMs are increasingly integrated into web-based systems for content summarization, yet their susceptibility to prompt injection attacks remains a pressing concern. In this study, we explore how non-visible HTML elements such as , aria-label, and alt attributes can be exploit...