LGMLNov 24, 2018

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+).

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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