Anomaly-based threat detection in smart health using machine learning
Background Anomaly detection is crucial in healthcare data due to challenges associated
with the integration of smart technologies and healthcare. Anomaly in electronic health …
with the integration of smart technologies and healthcare. Anomaly in electronic health …
RT-APT: A real-time APT anomaly detection method for large-scale provenance graph
Z Weng, W Zhang, T Zhu, Z Dou, H Sun, Z Ye… - Journal of Network and …, 2025 - Elsevier
Abstract Advanced Persistent Threats (APTs) are prevalent in the field of cyber attacks,
where attackers employ advanced techniques to control targets and exfiltrate data without …
where attackers employ advanced techniques to control targets and exfiltrate data without …
Healthcare insurance fraud detection using data mining
Background Healthcare programs and insurance initiatives play a crucial role in ensuring
that people have access to medical care. There are many benefits of healthcare insurance …
that people have access to medical care. There are many benefits of healthcare insurance …
Self-supervised multi-hop heterogeneous hypergraph embedding with informative pooling for graph-level classification
In heterogeneous graph analysis, existing self-supervised learning (SSL) methods face
several key challenges. Primarily, these approaches are tailored for node-level tasks and fail …
several key challenges. Primarily, these approaches are tailored for node-level tasks and fail …