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Security of Smart Home Intrusion Detection Systems using Data Mining Technique

Queen .U. Agunya1 , N.D. Nwiabu2

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-6 , Page no. 1169-1176, Jun-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i6.11691176

Online published on Jun 30, 2019

Copyright © Queen .U. Agunya, N.D. Nwiabu . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Queen .U. Agunya, N.D. Nwiabu, “Security of Smart Home Intrusion Detection Systems using Data Mining Technique,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.1169-1176, 2019.

MLA Style Citation: Queen .U. Agunya, N.D. Nwiabu "Security of Smart Home Intrusion Detection Systems using Data Mining Technique." International Journal of Computer Sciences and Engineering 7.6 (2019): 1169-1176.

APA Style Citation: Queen .U. Agunya, N.D. Nwiabu, (2019). Security of Smart Home Intrusion Detection Systems using Data Mining Technique. International Journal of Computer Sciences and Engineering, 7(6), 1169-1176.

BibTex Style Citation:
@article{Agunya_2019,
author = {Queen .U. Agunya, N.D. Nwiabu},
title = {Security of Smart Home Intrusion Detection Systems using Data Mining Technique},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2019},
volume = {7},
Issue = {6},
month = {6},
year = {2019},
issn = {2347-2693},
pages = {1169-1176},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4702},
doi = {https://doi.org/10.26438/ijcse/v7i6.11691176}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i6.11691176}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4702
TI - Security of Smart Home Intrusion Detection Systems using Data Mining Technique
T2 - International Journal of Computer Sciences and Engineering
AU - Queen .U. Agunya, N.D. Nwiabu
PY - 2019
DA - 2019/06/30
PB - IJCSE, Indore, INDIA
SP - 1169-1176
IS - 6
VL - 7
SN - 2347-2693
ER -

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Abstract

Poor security of Smart homes resulting from compromised system password and IP address has been on the increase as a result of hackers’ access to system. For this reason, there is need to introduce tertiary security feature. This work presents comprehensive survey of security challenges in smart home intrusion detection systems using qualitative research methodology. The researcher provided design of tertiary security parameter- Soft token along side IP address and password that serve as primary and secondary parameters to optimize system. Object oriented analysis and design plan was similarly embraced to help indicate the relationship between object and its class. K-means algorithm as data mining clustering technique was used to aid intrusion detection and prevention in smart home i.e. the system was able to differentiate between authorized from unauthorized access and simultaneously, send security warning to the framework administrator’s email whenever there is an intrusion. The development stage was done using some sets of software tools: PHP, HTML, JavaScript, and MySQL database system. Xampp server was used to test-run the system during the development process. Experimental result shows that soft token alongside IP address and password to check for an intrusion was able to optimize security.

Key-Words / Index Term

Smart Home, Intrusion Detection systems, K-Means algorithm, Password, Security, Soft token

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