Measuring the Functionality of Amazon Alexa and Google Home Applications

Voice Personal Assistant (VPA) is a software agent, which can interpret the user's voice commands and respond with appropriate information or action. The users can operate the VPA by voice to complete multiple tasks, such as read the message, order coffee, send an email, check the news, and so on. Although this new technique brings in interesting and useful features, they also pose new privacy and security risks. The current researches have focused on proof-of-concept attacks by pointing out the potential ways of launching the attacks, e.g., craft hidden voice commands to trigger malicious actions without noticing the user, fool the VPA to invoke the wrong applications. However, lacking a comprehensive understanding of the functionality of the skills and its commands prevents us from analyzing the potential threats of these attacks systematically. In this project, we developed convolutional neural networks with active learning and keyword-based approach to investigate the commands according to their capability (information retrieval or action injection) and sensitivity (sensitive or nonsensitive). Through these two levels of analysis, we will provide a complete view of VPA skills, and their susceptibility to the existing attacks.

Name thesis:degree_name

M.S.

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Computer Science

Department dc:contributor.department

Computer Science and Application

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2020

Author dc:creator

• Wang, Jiamin

Chair dc:contributor.committeechair

• Wang, Gang Alan

Committee members dc:contributor.committeemember

• Xin, Hongliang
• Bimal, Viswanath

• Natural Language Processing
• convolutional neural networks
• Active learning
• RAKE
• security

Statement dc:rights

• Creative Commons Attribution-ShareAlike 4.0 International

Licence dc:rights.uri

• http://creativecommons.org/licenses/by-sa/4.0/

Language dc:language.iso

en_US

Handle dc:identifier.uri

http://hdl.handle.net/10919/97316

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/97316