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Systematic Security Guideline Framework through Intelligently Automated Vulnerability Analysis

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摘要 This research aims to propose a practical framework designed for the automatic analysis of a product’s comprehensive functionality and security vulnerabilities,generating applicable guidelines based on real-world software.The existing analysis of software security vulnerabilities often focuses on specific features or modules.This partial and arbitrary analysis of the security vulnerabilities makes it challenging to comprehend the overall security vulnerabilities of the software.The key novelty lies in overcoming the constraints of partial approaches.The proposed framework utilizes data from various sources to create a comprehensive functionality profile,facilitating the derivation of real-world security guidelines.Security guidelines are dynamically generated by associating functional security vulnerabilities with the latest Common Vulnerabilities and Exposure(CVE)and Common Vulnerability Scoring System(CVSS)scores,resulting in automated guidelines tailored to each product.These guidelines are not only practical but also applicable in real-world software,allowing for prioritized security responses.The proposed framework is applied to virtual private network(VPN)software,wherein a validated Level 2 data flow diagram is generated using the Spoofing,Tampering,Repudiation,Information Disclosure,Denial of Service,and Elevation of privilege(STRIDE)technique with references to various papers and examples from related software.The analysis resulted in the identification of a total of 121 vulnerabilities.The successful implementation and validation demonstrate the framework’s efficacy in generating customized guidelines for entire systems,subsystems,and selected modules.
出处 《Computers, Materials & Continua》 SCIE EI 2024年第3期3867-3889,共23页 计算机、材料和连续体(英文)
基金 This work is the result of commissioned research project supported by the Affiliated Institute of ETRI(2022-086)received by Junho Ahn This research was supported by the National Research Foundation of Korea(NRF)Basic Science Research Program funded by the Ministry of Education(No.2020R1A6A1A03040583) this work was supported by Korea Institute for Advancement of Technology(KIAT)Grant funded by the Korea government(MOTIE)(P0008691,HRD Program for Industrial Innovation).
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