Detection and Prevention of Replay Attacks in  LoRaWAN Using Machine Learning

dc.contributor.author	Shahid, Abdul Samad Bin
dc.date.accessioned	2023-07-20T10:53:08Z
dc.date.available	2023-07-20T10:53:08Z
dc.date.issued	2020
dc.identifier.other	203905
dc.identifier.uri	http://10.250.8.41:8080/xmlui/handle/123456789/34878
dc.description	Supervisor: Dr. Muazzam Ali Khan Khattak	en_US
dc.description.abstract	LoRaWAN is a very popular globally adopted protocol for IOT networks. Despite many security measures introduced, there are still some flaws one of which is replay attacks. These attacks are a serious threat for the network traffic. Many solutions have been proposed for different scenarios of replay attacks, but till now no solution has been declared complete. In this paper we have analyzed different possible scenarios of replay attack and later compare the propose solutions. We have also proposed machine learning based solution.	en_US
dc.language.iso	en	en_US
dc.publisher	School of Electrical Engineering and Computer Science (SEECS), NUST	en_US
dc.subject	IOT, Machine Learning, Cyber Security, LORAWAN	en_US
dc.title	Detection and Prevention of Replay Attacks in LoRaWAN Using Machine Learning	en_US
dc.type	Thesis	en_US