APT Detection

Advanced Persistent Threat (APT) detection focuses on identifying sophisticated, long-term cyberattacks that evade traditional security measures. Current research heavily utilizes machine learning, employing deep learning architectures like convolutional neural networks, autoencoders, and transformers, often applied to provenance graphs representing system activity to improve detection accuracy and reduce false positives. These methods aim to enhance the speed and effectiveness of threat identification, providing security teams with actionable insights and facilitating faster response times to minimize damage. The field is actively exploring techniques to improve model interpretability and adaptability to evolving attack strategies, ultimately contributing to more robust and resilient cybersecurity systems.