Rejoinder to 'Statistical learning methods for information security: Fundamentals and case studies'

Hsing Kuo Pao, Yuh-Jye Lee, Chun-Ying Huang

Research output: Contribution to journalReview article

3 Scopus citations

Abstract

Hsing-Kuo-Pao and Yuh-Jye-Lee, Department of Computer Science and Information Engineering National Taiwan University of Science and Technology, Taiwan, provide more details about information security and security issues. Given the more and more sophisticated technology crossing so many diverse domains, a simple ignorance or lack of expertise can allow intrusions to bypass the defense systems. This is why both intruders and defenders focus more on automatic or learning procedures now rather than the traditional expert-centric defense systems for their tasks. Pao and researchers introduced the fundamentals and basic concepts for those who may be interested in using learning methods to solve information security problems but find no comprehensive material to tell them how to start with. It is worth discussing further recent learning research that is considered valuable in these years. For security problems, one viewpoint of utilizing learning methods is not to use accuracy and related assessment as the sole criterion to choose the best learning methods. On the other hand, training and prediction on different data distributions can lead to unexpected prediction performance, and it may not imply that the chosen method is not suitable for the use.

Original languageEnglish
Pages (from-to)119-121
Number of pages3
JournalApplied Stochastic Models in Business and Industry
Volume31
Issue number2
DOIs
StatePublished - 1 Mar 2015

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