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A hybrid approach to operating system discovery based on diagnosis
Author(s) -
Gag F.,
Esfandiari B.
Publication year - 2011
Publication title -
international journal of network management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.373
H-Index - 28
eISSN - 1099-1190
pISSN - 1055-7148
DOI - 10.1002/nem.751
Subject(s) - computer science , unification , simple (philosophy) , knowledge extraction , data science , artificial intelligence , machine learning , programming language , philosophy , epistemology
The objective of operating system (OS) discovery is to find which OSs are running on computers in a given network. There are two existing strategies for OS discovery—active and passive—each having fundamental limitations. This paper discusses how the theory of diagnosis can be used to address, in a simple and elegant way, the problems associated with OS discovery. The problems are formalized in a logical framework and solutions are obtained through automated reasoning. The result of using such a knowledge‐oriented approach is a natural unification of the active and passive methods of OS discovery in a hybrid approach. This paper also illustrates the benefits of the hybrid approach by comparing its accuracy with other existing OS discovery tools through a large‐scale experiment.