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Evaluating accuracy in prudence analysis for cyber security

Version 2 2024-06-04, 15:50
Version 1 2018-06-12, 09:57
conference contribution
posted on 2024-06-04, 15:50 authored by O Maruatona, P Vamplew, Richard DazeleyRichard Dazeley, PA Watters
Conventional Knowledge-Based Systems (KBS) have no way of detecting or signalling when their knowledge is insufficient to handle a case. Consequently, these systems may produce an uninformed conclusion when presented with a case beyond their current knowledge (brittleness) which results in the KBS giving incorrect conclusions due to insufficient knowledge or ignorance on a specific case. Prudence Analysis (PA) has been shown to be a viable alternative to brittleness in Ripple Down Rules (RDR) knowledge bases. To date, there have been two approaches to Prudence; attribute-based and structural-based prudence. This paper introduces Integrated Prudence Analysis (IPA), a novel Prudence method formed by combining these methods.

History

Volume

10638

Pagination

407-417

Location

Guangzhou, China

Start date

2017-11-14

End date

2017-11-18

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783319701387

ISBN-10

3319701398

Language

eng

Publication classification

E Conference publication, E1.1 Full written paper - refereed

Copyright notice

2017, Springer International Publishing AG

Title of proceedings

ICONIP 2017 : Proceedings of the Neural Information Processing International Conference

Event

Neural Information Processing. International Conference (24th : 2017 : Guangzhou, China)

Publisher

Springer

Place of publication

Cham, Switzerland

Series

Lecture notes in computer science