Context-aware security involving access control for smart homes

The explosive growth of the field of IoT. The smart home continues to rise in popularity, with a number of nodes that outnumber the population of the cities. This brings a rising interest in smart home security. While smart home security systems have been made before, a true context-aware home secur...

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Main Authors: Bartolome, Carissa M., Lim, Linus Austin, Soler, Javier Alfonso Enrique
Format: text
Language:English
Published: Animo Repository 2023
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Online Access:https://animorepository.dlsu.edu.ph/etdb_comtech/9
https://animorepository.dlsu.edu.ph/context/etdb_comtech/article/1017/viewcontent/Context_aware_security_involving_access_control_for_smart_homes_Redacted.pdf
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etdb_comtech-10172023-09-07T01:11:28Z Context-aware security involving access control for smart homes Bartolome, Carissa M. Lim, Linus Austin Soler, Javier Alfonso Enrique The explosive growth of the field of IoT. The smart home continues to rise in popularity, with a number of nodes that outnumber the population of the cities. This brings a rising interest in smart home security. While smart home security systems have been made before, a true context-aware home security system that can provide a new level of access control faces several issues stemming from the chaos of the home environment. The paper observed and collected data from a home environment using a network of ESP32 sensors. The data was preprocessed and run through several machine learning algorithms to find a series of attributes that were most helpful in access control for a smart home. Among the observed attributes, attributes that help identify appliances with lots of limits to who can access them such as Object IDs, Object Type, and Location have been observed to be integral to access control. Adjacent attributes such as Participant IDs with low privilege have also been observed to be useful in access control by various machine learning algorithms. Performing a Principal Component Analysis shows that these attributes are also important in describing the data collected. The study achieved its objectives where it identified Object IDs, Object Type, and Location as attributes that are useful in access control in a context-aware environment. Nonetheless, it's crucial to acknowledge that the attributes identified may differ based on the particular context and environment. As such, while these findings hold true within the scope of this study, varying contexts could result in a different set of significant attributes. 2023-08-02T07:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/etdb_comtech/9 https://animorepository.dlsu.edu.ph/context/etdb_comtech/article/1017/viewcontent/Context_aware_security_involving_access_control_for_smart_homes_Redacted.pdf Computer Technology Bachelor's Theses English Animo Repository Context-aware computing Home automation Home computer networks Information Security
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Context-aware computing
Home automation
Home computer networks
Information Security
spellingShingle Context-aware computing
Home automation
Home computer networks
Information Security
Bartolome, Carissa M.
Lim, Linus Austin
Soler, Javier Alfonso Enrique
Context-aware security involving access control for smart homes
description The explosive growth of the field of IoT. The smart home continues to rise in popularity, with a number of nodes that outnumber the population of the cities. This brings a rising interest in smart home security. While smart home security systems have been made before, a true context-aware home security system that can provide a new level of access control faces several issues stemming from the chaos of the home environment. The paper observed and collected data from a home environment using a network of ESP32 sensors. The data was preprocessed and run through several machine learning algorithms to find a series of attributes that were most helpful in access control for a smart home. Among the observed attributes, attributes that help identify appliances with lots of limits to who can access them such as Object IDs, Object Type, and Location have been observed to be integral to access control. Adjacent attributes such as Participant IDs with low privilege have also been observed to be useful in access control by various machine learning algorithms. Performing a Principal Component Analysis shows that these attributes are also important in describing the data collected. The study achieved its objectives where it identified Object IDs, Object Type, and Location as attributes that are useful in access control in a context-aware environment. Nonetheless, it's crucial to acknowledge that the attributes identified may differ based on the particular context and environment. As such, while these findings hold true within the scope of this study, varying contexts could result in a different set of significant attributes.
format text
author Bartolome, Carissa M.
Lim, Linus Austin
Soler, Javier Alfonso Enrique
author_facet Bartolome, Carissa M.
Lim, Linus Austin
Soler, Javier Alfonso Enrique
author_sort Bartolome, Carissa M.
title Context-aware security involving access control for smart homes
title_short Context-aware security involving access control for smart homes
title_full Context-aware security involving access control for smart homes
title_fullStr Context-aware security involving access control for smart homes
title_full_unstemmed Context-aware security involving access control for smart homes
title_sort context-aware security involving access control for smart homes
publisher Animo Repository
publishDate 2023
url https://animorepository.dlsu.edu.ph/etdb_comtech/9
https://animorepository.dlsu.edu.ph/context/etdb_comtech/article/1017/viewcontent/Context_aware_security_involving_access_control_for_smart_homes_Redacted.pdf
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