NURSE: eNd-UseR IoT malware detection tool for Smart homEs

NURSE: eNd-UseR IoT malware detection tool for Smart homEs

d' Estalenx, Antoine (TU Delft Electrical Engineering, Mathematics and Computer Science)

Hernandez Ganan, C. (mentor)
Verwer, S.E. (graduation committee)
Cockx, J.G.H. (graduation committee)

Delft University of Technology

Computer Science | Cyber Security

2021-08-24

IoT devices keep entering our homes with the promise of delivering more services and enhancing user experience; however, these new devices also carry along an alarming number of vulnerabilities and security issues. In most cases, the users of these devices are completely unaware of the security risks that connecting these devices entail. Current tools do not provide users with essential security information such as whether a device is infected with malware. Traditional techniques to detect malware infections were not meant to be used by the end-user and current malware removal tools and security software cannot handle the heterogeneity of IoT devices. In this report, we design, develop and evaluate a tool, called NURSE, to fill this information gap, i.e., enabling end-users to detect IoT-malware infections in their home networks. NURSE follows a modular approach to analyze IoT traffic as captured by means of an ARP spoofing technique which does not require any network modification or specific hardware. Thus, NURSE provides zero-configuration IoT traffic analysis within everybody's reach. After testing NURSE in 83 different IoT network scenarios with a wide variety of IoT device types, results show that NURSE identifies malware-infected IoT devices with high-accuracy (86.7%) using device network behaviour and contacted destinations.

cybersecurity
network security
botnet
IoT
Internet of Things
Smart Homes

http://resolver.tudelft.nl/uuid:d55a20d4-2f9a-4409-b102-18e047b11895

Student theses

master thesis

© 2021 Antoine d' Estalenx