Skip to main content

Research Repository

Advanced Search

Evaluating awareness and perception of botnet activity within consumer Internet-of-Things (IoT) networks.

McDermott, Christopher D.; Isaacs, John P.; Petrovski, Andrei V.

Authors

Christopher D. McDermott



Abstract

The growth of the Internet of Things (IoT), and demand for low-cost, easy-to-deploy devices, has led to the production of swathes of insecure Internet-connected devices. Many can be exploited and leveraged to perform large-scale attacks on the Internet, such as those seen by the Mirai botnet. This paper presents a cross-sectional study of how users value and perceive security and privacy in smart devices found within the IoT. It analyzes user requirements from IoT devices, and the importance placed upon security and privacy. An experimental setup was used to assess user ability to detect threats, in the context of technical knowledge and experience. It clearly demonstrated that without any clear signs when an IoT device was infected, it was very difficult for consumers to detect and be situationally aware of threats exploiting home networks. It also demonstrated that without adequate presentation of data to users, there is no clear correlation between level of technical knowledge and ability to detect infected devices.

Citation

MCDERMOTT, C.D., ISAACS, J.P. and PETROVSKI, A.V. 2019. Evaluating awareness and perception of botnet activity within consumer Internet-of-Things (IoT) networks. Informatics [online], 6(1), article 8. Available from: https://doi.org/10.3390/informatics6010008

Journal Article Type Article
Acceptance Date Feb 11, 2019
Online Publication Date Feb 18, 2019
Publication Date Mar 31, 2019
Deposit Date Jul 12, 2019
Publicly Available Date Jul 15, 2019
Journal Informatics
Electronic ISSN 2227-9709
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 6
Issue 1
Article Number 8
DOI https://doi.org/10.3390/informatics6010008
Keywords Internet of Things; Situational awareness; Threat detection; IoT security; Botnet; DDoS
Public URL https://rgu-repository.worktribe.com/output/321753

Files





You might also like



Downloadable Citations