OCLEP+: One-class Anomaly and Intrusion Detection Using Minimal Length of Emerging Patterns
arXiv:1811.09842v16 citations
Originality Synthesis-oriented
AI Analysis
This addresses anomaly detection for security applications, but appears incremental as it builds on existing pattern-based methods.
The paper tackles the problem of one-class anomaly and intrusion detection by introducing OCLEP+, a method based on minimal length of emerging patterns, but the abstract lacks specific results or numbers.
This paper presents a method called One-class Classification using Length statistics of Emerging Patterns Plus (OCLEP+).