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Security Requirement Recommendation Method Using Case-Based Reasoning to Prevent Advanced Persistent Threatsoa mark
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Publication Year
2023-02-01
Publisher
MDPI
Citation
Applied Sciences (Switzerland), Vol.13
Keyword
advanced persistent threatartificial intelligencecase-based reasoningproblem domain ontologyrecommendation systemsecurity requirement
All Science Classification Codes (ASJC)
Materials Science (all)InstrumentationEngineering (all)Process Chemistry and TechnologyComputer Science ApplicationsFluid Flow and Transfer Processes
Abstract
As the world becomes digitized and connected, cyberattacks and security issues have been steadily increasing. In particular, advanced persistent threats (APTs) are actors who perform various complex attacks over the long term to achieve their purpose. These attacks involve more planning and intelligence than typical cyberattacks. Many studies have investigated APT detection and defense methods; however, studies on security requirements that focus on non-technical factors and prevention are relatively few. Therefore, this study aims to provide attack information to users obtained by analyzing attack scenarios as well as security requirements to help the users understand and make decisions. To this end, we propose a method for extracting attack elements by providing users with templates for attack scenarios with different levels of abstraction. In addition, we use a problem domain ontology that is based on the concept of a case to provide users with attack analysis results and recommended security requirements. Our method uses case-based reasoning to retrieve similar cases, recommend reusable security requirements, and propose revision directions. The ontology can be improved by adding the solution to the problem as a new case. We conducted case studies and surveys to evaluate our methods and showed that they help specify security requirements.
ISSN
2076-3417
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/33243
DOI
https://doi.org/10.3390/app13031505
Fulltext

Type
Article
Funding
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Science and ICT (NRF-2020R1F1A1075605), and the BK21 FOUR program of the National Research Foundation of Korea, funded by the Ministry of Education (NRF5199991014091).
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Lee, Seok-Won Image
Lee, Seok-Won이석원
Department of Software and Computer Engineering
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