Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Digital forensic approaches for Amazon Alexa ecosystem

Full metadata record
DC Field Value Language
dc.contributor.authorChung, Hyunji-
dc.contributor.authorPark, Jungheum-
dc.contributor.authorLee, Sangjin-
dc.date.accessioned2021-09-03T03:40:46Z-
dc.date.available2021-09-03T03:40:46Z-
dc.date.created2021-06-16-
dc.date.issued2017-08-
dc.identifier.issn1742-2876-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/82759-
dc.description.abstractInternet of Things (IoT) devices such as the Amazon Echo - a smart speaker developed by Amazon - are undoubtedly great sources of potential digital evidence due to their ubiquitous use and their always-on mode of operation, constituting a human-life's black box. The Amazon Echo in particular plays a centric role for the cloud-based intelligent virtual assistant (IVA) Alexa developed by Amazon Lab126. The Alexa-enabled wireless smart speaker is the gateway for all voice commands submitted to Alexa. Moreover, the IVA interacts with a plethora of compatible IoT devices and third-party applications that leverage cloud resources. Understanding the complex cloud ecosystem that allows ubiquitous use of Alexa is paramount on supporting digital investigations when need raises. This paper discusses methods for digital forensics pertaining to the IVA Alexa's ecosystem. The primary contribution of this paper consists of a new efficient approach of combining cloud-native forensics with client-side forensics (forensics for companion devices), to support practical digital investigations. Based on a deep understanding of the targeted ecosystem, we propose a proof-of-concept tool, CIFT, that supports identification, acquisition and analysis of both native artifacts from the cloud and client-centric artifacts from local devices (mobile applications and web browsers). (C) 2017 The Author(s). Published by Elsevier Ltd. on behalf of DFRWS.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER SCI LTD-
dc.titleDigital forensic approaches for Amazon Alexa ecosystem-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, Sangjin-
dc.identifier.doi10.1016/j.diin.2017.06.010-
dc.identifier.scopusid2-s2.0-85026735513-
dc.identifier.wosid000407728500003-
dc.identifier.bibliographicCitationDIGITAL INVESTIGATION, v.22, pp.S15 - S25-
dc.relation.isPartOfDIGITAL INVESTIGATION-
dc.citation.titleDIGITAL INVESTIGATION-
dc.citation.volume22-
dc.citation.startPageS15-
dc.citation.endPageS25-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.subject.keywordAuthorInternet of Things-
dc.subject.keywordAuthorCloud-based IoT-
dc.subject.keywordAuthorIntelligent virtual assistant (IVA)-
dc.subject.keywordAuthorAmazon Alexa-
dc.subject.keywordAuthorAmazon Echo-
dc.subject.keywordAuthorCloud native forensics-
dc.subject.keywordAuthorClient centric forensics-
dc.subject.keywordAuthorCIFT-
Files in This Item
There are no files associated with this item.
Appears in
Collections
School of Cyber Security > Department of Information Security > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher LEE, SANG JIN photo

LEE, SANG JIN
정보보호학과
Read more

Altmetrics

Total Views & Downloads

BROWSE