Url Detection

URL detection focuses on automatically identifying malicious URLs (e.g., phishing, malware) to enhance online security. Current research emphasizes developing robust and explainable models, employing architectures like large language models (LLMs), ensemble trees, and optimized gradient boosting classifiers, often incorporating techniques like contrastive learning and adversarial training to improve generalization and resilience against evasion tactics. These advancements are crucial for mitigating the ever-evolving threat landscape of online malicious activity and improving the effectiveness of real-time security measures across various platforms.