J. D. Verdejo

Artificial Intelligence · 2009

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 11 citations into it; #14,298 of 35,345 by trust here, #12,761 by citations
• Computer Networks and Communications — 11 citations into it; #3,241 of 9,886 by trust here, #2,242 by citations
• Signal Processing — 7 citations into it

Whom J. D. Verdejo trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. William W. Cohen
2. Dit-Yan Yeung
3. Yihua Liao
4. Hervé Debar
5. Richard P. Lippmann

Who trusts J. D. Verdejo overall

1. Chaouki Khammassi
2. Paulo Angelo Alves Resende
3. Thanh Thi Nguyen
4. Jonathan J. Davis
5. V. Varadharajan
6. Asaf Shabtai
7. Preeti Mishra
8. Nasrin Sultana
9. Nickolaos Koroniotis
10. Yisroel Mirsky

Papers from J. D. Verdejo's perspective

Ordered by how strongly the researchers J. D. Verdejo trusts endorse each paper. Same corpus, a different order for every researcher.

1. Fast Effective Rule Induction
2. Use of K-Nearest Neighbor classifier for intrusion detection (Computers & security)
3. The 1999 DARPA off-line intrusion detection evaluation (Comput. Networks)
4. Specification-based anomaly detection: a new approach for detecting network intrusions (Conference on Computer and Communications Security)
5. A neural network component for an intrusion detection system
6. Cost-based modeling for fraud and intrusion detection: results from the JAM project (Proceedings DARPA Information Survivability Conference and Exposition. DISCEX'00)
7. LOF: identifying density-based local outliers
8. Host-based intrusion detection using dynamic and static behavioral models (Pattern Recognition)
9. Bayesian event classification for intrusion detection (19th Annual Computer Security Applications Conference, 2003. Proceedings.)
10. Using Genetic Algorithm for Network Intrusion Detection

Their papers

• Anomaly-based network intrusion detection: Techniques, systems and challenges (2009) — 2,264 citations