Robustness Analysis of Machine Learning Models for IoT Intrusion Detection under Data Poisoning Attacks

Ensuring the reliability of machine learning-based intrusion detection systems remains a critical challenge in Internet of Things IoT environments, particularly as data poisoning attacks increasingly threaten the integrity of model training pipelines. This study evaluates the susceptibility of fo...

Scam Shield: Multi-Model Voting and Fine-Tuned LLMs against Adversarial Attacks

Scam detection remains a critical challenge in cybersecurity as adversaries craft messages that evade automated filters. We propose a Hierarchical Scam Detection System HSDS that combines a lightweight multi-model voting front end with a fine-tuned LLaMA 3.1 8B Instruct back end to improve accura...