Abstract
Internet 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).
Original language | English |
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Pages | S15-S25 |
DOIs | |
Publication status | Published - 2017 |
Event | 17th Annual DFRWS USA, DFRWS 2017 USA - Austin, United States Duration: 2017 Aug 6 → 2017 Aug 9 |
Conference
Conference | 17th Annual DFRWS USA, DFRWS 2017 USA |
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Country/Territory | United States |
City | Austin |
Period | 17/8/6 → 17/8/9 |
Bibliographical note
Publisher Copyright:© 2017 The Author(s). Published by Elsevier Ltd. on behalf of DFRWS.
Keywords
- Amazon Alexa
- Amazon echo
- CIFT
- Client centric forensics
- Cloud native forensics
- Cloud-based IoT
- Intelligent virtual assistant (IVA)
- Internet of things
ASJC Scopus subject areas
- Information Systems