Visible to the public Security Patterns from Intelligent Data: A Map of Software Vulnerability Analysis

TitleSecurity Patterns from Intelligent Data: A Map of Software Vulnerability Analysis
Publication TypeConference Paper
Year of Publication2017
AuthorsJinan, S., Kefeng, P., Xuefeng, C., Junfu, Z.
Conference Name2017 ieee 3rd international conference on big data security on cloud (bigdatasecurity), ieee international conference on high performance and smart computing (hpsc), and ieee international conference on intelligent data and security (ids)
Date Publishedmay
ISBN Number978-1-5090-6296-6
KeywordsAnalytical models, composability, compositionality, Computational Intelligence, cryptography, Data models, Databases, Industries, intelligent data, intelligent data analysis, intelligent data processing, program analysis, pubcrawl, security, security of data, security patterns, security vulnerability, Software, Software Vulnerability, software vulnerability analysis, Taxonomy
Abstract

A significant milestone is reached when the field of software vulnerability research matures to a point warranting related security patterns represented by intelligent data. A substantial research material of empirical findings, distinctive taxonomy, theoretical models, and a set of novel or adapted detection methods justify a unifying research map. The growth interest in software vulnerability is evident from a large number of works done during the last several decades. This article briefly reviews research works in vulnerability enumeration, taxonomy, models and detection methods from the perspective of intelligent data processing and analysis. This article also draws the map which associated with specific characteristics and challenges of vulnerability research, such as vulnerability patterns representation and problem-solving strategies.

URLhttps://ieeexplore.ieee.org/document/7980310/
DOI10.1109/BigDataSecurity.2017.9
Citation Keyjinan_security_2017