Security of Smart Home Intrusion Detection Systems using Data Mining Technique - Agunya, Queen U; ND, Nwiabu (International Journal of Computer Sciences and Engineering, 2019)
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.