Non-Invasive Challenge Response Authentication for Voice Transactions with Smart Home Behavior.

Sensors
Victor Hayashi, Wilson Ruggiero

Abstract

Smart speakers, such as Alexa and Google Home, support daily activities in smart home environments. Even though voice commands enable friction-less interactions, existing financial transaction authorization mechanisms hinder usability. A non-invasive authorization by leveraging presence and light sensors' data is proposed in order to replace invasive procedure through smartphone notification. The Coloured Petri Net model was created for synthetic data generation, and one month data were collected in test bed with real users. Random Forest machine learning models were used for smart home behavior information retrieval. The LSTM prediction model was evaluated while using test bed data, and an open dataset from CASAS. The proposed authorization mechanism is based on Physical Unclonable Function usage as a random number generator seed in a Challenge Response protocol. The simulations indicate that the proposed scheme with specialized autonomous device could halve the total response time for low value financial transactions triggered by voice, from 7.3 to 3.5 s in a non-invasive manner, maintaining authorization security.

References

May 19, 2009·Methods of Information in Medicine·Diane J Cook, M Schmitter-Edgecombe
Jul 31, 2009·Technology and Health Care : Official Journal of the European Society for Engineering and Medicine·S SzewcyzkD Cook
Jun 19, 2015·Sensors·Jonathan SynnottPaul Jeffers
Apr 1, 2017·Sensors·Jessamyn DahmenXiaobo Wang

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Methods Mentioned

BETA
chip

Software Mentioned

Capital One Alexa Skill
Simulink
CPN ML
MySQL
Snips
Alexa
OWASP
MATLAB
gar2out
Axis Bank Alexa Skill Alexa Skill

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