Cited 0 time in
Effective and efficient detection of software theft via dynamic API authority vectors
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Chae, Dong-Kyu | - |
| dc.contributor.author | Kim, Sang-Wook | - |
| dc.contributor.author | Cho, Seong-Je | - |
| dc.contributor.author | Kim, Yesol | - |
| dc.date.accessioned | 2022-07-15T19:58:39Z | - |
| dc.date.available | 2022-07-15T19:58:39Z | - |
| dc.date.issued | 2015-12 | - |
| dc.identifier.issn | 0164-1212 | - |
| dc.identifier.issn | 1873-1228 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/155706 | - |
| dc.description.abstract | Software theft has become a very serious threat to both the software industry and individual software developers. A software birthmark indicates unique characteristics of a program in question, which can be used for analyzing the similarity of a pair of programs and detecting theft. This paper proposes a novel birthmark, a dynamic API authority vector (DAAV). DAAV satisfies four essential requirements for good birthmarks credibility, resiliency, scalability, and packing-free while existing static birthmarks are unable to handle the packed programs and existing dynamic birthmarks do not satisfy credibility and resiliency. Through our extensive experiments with a set of Windows applications, DAAV is shown to have not only the credibility and resiliency higher than the existing dynamic birthmarks but also the accuracy comparable to that of existing static birthmarks. This result indicates that our proposed birthmark provides high accuracy and also covers packed programs successfully in detecting software theft. | - |
| dc.format.extent | 9 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | Elsevier BV | - |
| dc.title | Effective and efficient detection of software theft via dynamic API authority vectors | - |
| dc.type | Article | - |
| dc.publisher.location | 미국 | - |
| dc.identifier.doi | 10.1016/j.jss.2015.08.018 | - |
| dc.identifier.scopusid | 2-s2.0-84944061567 | - |
| dc.identifier.wosid | 000364244600001 | - |
| dc.identifier.bibliographicCitation | Journal of Systems and Software, v.110, pp 1 - 9 | - |
| dc.citation.title | Journal of Systems and Software | - |
| dc.citation.volume | 110 | - |
| dc.citation.startPage | 1 | - |
| dc.citation.endPage | 9 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Computer Science | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Software Engineering | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
| dc.subject.keywordPlus | Crime | - |
| dc.subject.keywordPlus | Software engineering | - |
| dc.subject.keywordAuthor | Birthmark | - |
| dc.subject.keywordAuthor | Software theft detection | - |
| dc.subject.keywordAuthor | Similarity analysis | - |
| dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S016412121500179X?via%3Dihub | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1366
COPYRIGHT © 2024 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.
