User profiling via application usage pattern on digital devices for digital forensics
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kwon, Hongkyun | - |
dc.contributor.author | Lee, Sangjin | - |
dc.contributor.author | Jeong, Doowon | - |
dc.date.accessioned | 2021-08-30T02:44:44Z | - |
dc.date.available | 2021-08-30T02:44:44Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2021-04-15 | - |
dc.identifier.issn | 0957-4174 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/49420 | - |
dc.description.abstract | In digital forensics, user profiling aims to predict characteristics of the user from digital evidence extracted from digital devices (e.g. smartphone, laptop, tablet). Previous researches showed promising results, but there are limitations to apply practical investigations. The researches so far have focused only on specific applications, devices, or operating systems by analyzing the order of execution or volatile data such as network traffic and online content. This paper introduces a user profiling method, named Entity Profiling with Binary Predicates (EPBP) model, which analyzes non-volatile data remained on digital devices. The proposed model defines that a user has two properties: tendency and impact, which indicate patterns of application usage. Based on the attributes, the EPBP model generates users' profiles and performs similarity analysis to differentiate between the users. We also present methods for clustering and anomaly detection through real case studies. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | PERGAMON-ELSEVIER SCIENCE LTD | - |
dc.title | User profiling via application usage pattern on digital devices for digital forensics | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, Sangjin | - |
dc.identifier.doi | 10.1016/j.eswa.2020.114488 | - |
dc.identifier.scopusid | 2-s2.0-85097716861 | - |
dc.identifier.wosid | 000615904500007 | - |
dc.identifier.bibliographicCitation | EXPERT SYSTEMS WITH APPLICATIONS, v.168 | - |
dc.relation.isPartOf | EXPERT SYSTEMS WITH APPLICATIONS | - |
dc.citation.title | EXPERT SYSTEMS WITH APPLICATIONS | - |
dc.citation.volume | 168 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Operations Research & Management Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Operations Research & Management Science | - |
dc.subject.keywordAuthor | User profiling | - |
dc.subject.keywordAuthor | Digital forensics | - |
dc.subject.keywordAuthor | Application usage | - |
dc.subject.keywordAuthor | User similarity | - |
dc.subject.keywordAuthor | Anomaly detection | - |
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