Rules-based Detection Systems
Rules-Based Detection Systems is a detection methodology that identifies suspicious activities by applying a predefined set of logical rules or heuristics to observed behaviors, distinguishing it from statistical or machine learning approaches through its reliance on explicit, human-encoded domain knowledge.
132
Publications
5.4K
Citations
398
Authors
187
Institutions
Publications per year
2017–2026
44
132
Intrusion Detection with Neural Networks
Jake Ryan, Meng-Jang Lin, Risto Miikkulainen · 1997 · 411 citations
Smokey: Automatic Recognition of Hostile Messages
Spertus · 1997 · 222 citations
Smokey: automatic recognition of hostile messages
Ellen Spertus · 1997 · 170 citations
Question analysis: How Watson reads a clue
Adam Lally, John Prager, Michael C. McCord et al. · IBM Journal of Research and Development · 2012 · 167 citations
1–5 of 132
398
4
h-index
3
h-index
3
h-index
3
h-index
2
h-index
1–5 of 398
187

University of Waterloo
Waterloo, Canada
3 h-index
3 publications
74 citations
Universidade Federal do Espírito Santo
Vitória, Brazil
3 h-index
10 publications
212 citations
Iowa State University
Ames, United States
2 h-index
8 publications
888 citations

Northeastern University
Shenyang, China
2 h-index
2 publications
47 citations

University of Milano-Bicocca
Milan, Italy
2 h-index
4 publications
55 citations
Arizona State University
Tempe, United States
2 h-index
2 publications
104 citations

Marche Polytechnic University
Ancona, Italy
2 h-index
1 publications
30 citations

University of Milan
Milan, Italy
2 h-index
4 publications
56 citations
1–8 of 187
4 publications · 187 citations
4
h-index
4 publications · 243 citations
4
h-index
2 publications · 61 citations
2
h-index
2 publications · 325 citations
2
h-index
TFS · 2 publications · 130 citations
2
h-index
1–5