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A Safe Collaborative Chatbot for Smart Home Assistants
Smart home assistants, which enable users to control home appliances and can be used for holding entertaining conversations, have become an inseparable part of many people’s homes. Recently, there have been many attempts to allow end-users to teach a home assistant new commands, responses, and rules...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512550/ https://www.ncbi.nlm.nih.gov/pubmed/34640960 http://dx.doi.org/10.3390/s21196641 |
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author | Chkroun, Merav Azaria, Amos |
author_facet | Chkroun, Merav Azaria, Amos |
author_sort | Chkroun, Merav |
collection | PubMed |
description | Smart home assistants, which enable users to control home appliances and can be used for holding entertaining conversations, have become an inseparable part of many people’s homes. Recently, there have been many attempts to allow end-users to teach a home assistant new commands, responses, and rules, which can then be shared with a larger community. However, allowing end-users to teach an agent new responses, which are shared with a large community, opens the gate to malicious users, who can teach the agent inappropriate responses in order to promote their own business, products, or political views. In this paper, we present a platform that enables users to collaboratively teach a smart home assistant (or chatbot) responses using natural language. We present a method of collectively detecting malicious users and using the commands taught by the malicious users to further mitigate activity of future malicious users. We ran an experiment with 192 subjects and show the effectiveness of our platform. |
format | Online Article Text |
id | pubmed-8512550 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-85125502021-10-14 A Safe Collaborative Chatbot for Smart Home Assistants Chkroun, Merav Azaria, Amos Sensors (Basel) Article Smart home assistants, which enable users to control home appliances and can be used for holding entertaining conversations, have become an inseparable part of many people’s homes. Recently, there have been many attempts to allow end-users to teach a home assistant new commands, responses, and rules, which can then be shared with a larger community. However, allowing end-users to teach an agent new responses, which are shared with a large community, opens the gate to malicious users, who can teach the agent inappropriate responses in order to promote their own business, products, or political views. In this paper, we present a platform that enables users to collaboratively teach a smart home assistant (or chatbot) responses using natural language. We present a method of collectively detecting malicious users and using the commands taught by the malicious users to further mitigate activity of future malicious users. We ran an experiment with 192 subjects and show the effectiveness of our platform. MDPI 2021-10-06 /pmc/articles/PMC8512550/ /pubmed/34640960 http://dx.doi.org/10.3390/s21196641 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chkroun, Merav Azaria, Amos A Safe Collaborative Chatbot for Smart Home Assistants |
title | A Safe Collaborative Chatbot for Smart Home Assistants |
title_full | A Safe Collaborative Chatbot for Smart Home Assistants |
title_fullStr | A Safe Collaborative Chatbot for Smart Home Assistants |
title_full_unstemmed | A Safe Collaborative Chatbot for Smart Home Assistants |
title_short | A Safe Collaborative Chatbot for Smart Home Assistants |
title_sort | safe collaborative chatbot for smart home assistants |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512550/ https://www.ncbi.nlm.nih.gov/pubmed/34640960 http://dx.doi.org/10.3390/s21196641 |
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