[3] A negative selection algorithm with hypercube interface detectors for anomaly detection. Applied Soft Computing (2024). [4] Negative Selection Algorithm Based on Antigen Density Clustering .

Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods which focused on characterizing past threats. Adaptive anomaly detection ...

Implement the anomaly detection algorithm which is widely used in fraud detection (e.g. ‘has this credit card been stolen?’) and apply it to detect failing servers on a network. And use collaborative ...

In recent years, air crashes have occurred frequently, which caused huge losses to life and property. Timely and effective anomaly detection is the premise in marine rescue and rescue (MSAR). The ...

The density of the points corresponds to the sparsity which was used for anomaly detection. High Resolution Image. ... To the best of our knowledge, this is the first study to apply the ...

Summary <p>Wireless Sensor Networks endure from a wide range of faults and anomalies which hinder their smooth working. Anomaly Detection (AD) in wireless sensor networks is a crucial research area, ...

[Jeong2023] WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation in CVPR, 2023. [Chen2024] CLIP-AD: A Language-Guided Staged Dual-Path Model for Zero-shot Anomaly Detection in Arxiv, 2024. ...

This becomes significant in light of the recent stampede in Karnataka's Bengaluru during the celebrations of the Royal Challengers Bengaluru's IPL victory that led to the death of 11 people and ...