Recent spectacular progress in computational technologies has led to an unprecedented
boom in the field of Artificial Intelligence (AI). AI is now used in a plethora of research areas …

Network intrusion detection system is an essential part of network security research. It
detects intrusion behaviors through active defense technology and takes emergency …

With the development of Raman spectroscopy and the expansion of its application domains,
conventional methods for spectral data analysis have manifested many limitations. Exploring …

Financial fraud, considered as deceptive tactics for gaining financial benefits, has recently
become a widespread menace in companies and organizations. Conventional techniques …

Due to unavailability of prior knowledge about anomalies, background suppression (BS) is a
crucial factor in anomaly detection (AD) evaluation. The difficulty in dealing with BS arises …

Abstract Space anomaly detection plays a critical role in safeguarding the integrity and
reliability of space systems amid the rising tide of threats. This survey aims to deepen …

Anomaly detection is a critical issue across several academic fields and real-world
applications. Artificial neural networks have been proposed to detect anomalies from …

This study explores the growing challenges of cybersecurity in the context of rapidly adopted
Internet of Things (IoT) technologies, which have become increasingly susceptible to cyber …

Anomaly detection has been used to detect and analyze anomalous elements from data for
years. Various techniques have been developed to detect anomalies. However, the most …

Environmental changes can profoundly impact the performance of artificial intelligence
systems operating in the real world, with effects ranging from overt catastrophic failures to …