Results 271 to 280 of about 352,249 (316)
Safeguarding against external intrusions utilizing adaptive bio-inspired multi-population anomaly detection for IoT network. [PDF]
Dwivedi S +3 more
europepmc +1 more source
UMIAD-EGMF: unsupervised medical image anomaly detection based on edge guidance and multi-scale flow fusion. [PDF]
Li Z, Lin G, Zhang D, Huang R, Yang J.
europepmc +1 more source
AI-driven cybersecurity framework for anomaly detection in power systems. [PDF]
V M V +4 more
europepmc +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Computer Fraud and Security, 2019
Due to the significance it holds in the concept of fraud, security in computers and business, anomaly detection serves very much purpose. Using techniques in unsupervised machine learning, the two algorithms applied in this study are Isolation Forest and Autoencoder in credit card fraud detection in financial datasets.
Gopinath Rebala +2 more
openaire +2 more sources
Due to the significance it holds in the concept of fraud, security in computers and business, anomaly detection serves very much purpose. Using techniques in unsupervised machine learning, the two algorithms applied in this study are Isolation Forest and Autoencoder in credit card fraud detection in financial datasets.
Gopinath Rebala +2 more
openaire +2 more sources
Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, 2016
This tutorial will present an overview of program anomaly detection, which analyzes normal program behaviors and discovers aberrant executions caused by attacks, misconfigurations, program bugs, and unusual usage patterns. It was first introduced as an analogy between intrusion detection for programs and the immune mechanism in biology. Advanced models
Xiaokui Shu, Danfeng Yao
openaire +1 more source
This tutorial will present an overview of program anomaly detection, which analyzes normal program behaviors and discovers aberrant executions caused by attacks, misconfigurations, program bugs, and unusual usage patterns. It was first introduced as an analogy between intrusion detection for programs and the immune mechanism in biology. Advanced models
Xiaokui Shu, Danfeng Yao
openaire +1 more source

