Detection Rule

Detection rules are algorithms and systems designed to identify specific patterns or anomalies within data, aiming to improve accuracy and efficiency in various applications. Current research focuses on enhancing detection capabilities through innovative model architectures, such as incorporating frequency domain analysis for improved video inpainting detection or leveraging large language models to automate rule extraction from unstructured cyber threat intelligence. These advancements are crucial for addressing challenges in diverse fields, ranging from cybersecurity and spam filtering to the detection of manipulated media and adversarial attacks on machine learning models, ultimately improving the reliability and security of numerous systems.