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Risk words suggestion for information security audit by Bayesian inference
Author(s) -
Satoh Naoki,
Samejima Masaki
Publication year - 2019
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.12133
Subject(s) - inference , audit , computer science , bayesian inference , word (group theory) , bayesian probability , natural language processing , audit risk , risk assessment , risk analysis (engineering) , artificial intelligence , actuarial science , accounting , business , computer security , linguistics , philosophy
We present risk word suggestion for enabling an auditor to identify potential risks based on words of identified risks in an audit report. Once the auditor describes the identified risks in the report, words related to the potential risks are inferred with words in the description of the identified risks, and suggested to the auditor. For the word inference, we assume that words of potential risks and identified risks are related to each other, and by applying Bayesian inference we reveal the relation between the words. In our evaluation experiments with real five cases, Bayesian inference can suggest the words for identifying potential risks. Furthermore, two auditors can accurately identify potential risks by the suggested words.