A4 Article in conference proceedings
Network anomaly detection in wireless sensor networks : a review (2019)


Leppänen, Rony Franca; Hämäläinen, Timo (2019). Network anomaly detection in wireless sensor networks : a review. In Galinina, Olga; Andreev, Sergey; Balandin, Sergey; Koucheryavy, Yevgeni (Eds.) NEW2AN 2019, ruSMART 2019 : Internet of Things, Smart Spaces, and Next Generation Networks and Systems : Proceedings of the 19th International Conference on Next Generation Wired/Wireless Networking, and 12th Conference on Internet of Things and Smart Spaces, Lecture Notes in Computer Science, 11660. Cham: Springer, 196-207. DOI: 10.1007/978-3-030-30859-9_17


JYU authors or editors


Publication details

All authors or editors: Leppänen, Rony Franca; Hämäläinen, Timo

Parent publication: NEW2AN 2019, ruSMART 2019 : Internet of Things, Smart Spaces, and Next Generation Networks and Systems : Proceedings of the 19th International Conference on Next Generation Wired/Wireless Networking, and 12th Conference on Internet of Things and Smart Spaces

Parent publication editors: Galinina, Olga; Andreev, Sergey; Balandin, Sergey; Koucheryavy, Yevgeni

Place and date of conference: St.Petersburg, Russia, 26.-28.8.2019

ISBN: 978-3-030-30858-2

eISBN: 978-3-030-30859-9

Journal or series: Lecture Notes in Computer Science

ISSN: 0302-9743

eISSN: 1611-3349

Publication year: 2019

Number in series: 11660

Pages range: 196-207

Number of pages in the book: 797

Publisher: Springer

Place of Publication: Cham

Publication country: Switzerland

Publication language: English

DOI: http://doi.org/10.1007/978-3-030-30859-9_17

Open Access: Publication channel is not openly available


Abstract

Wireless sensor networks function as one of the enablers for the large-scale deployment of Internet of Things in various applications, including critical infrastructure. However, the open communications environment of wireless systems, immature technologies and the inherent limitations of sensor nodes make wireless sensor networks an attractive target to malicious activities. The main contributions of this review include describing the true nature of wireless sensor networks through their characteristics and security threats as well as reflecting them to network anomaly detection by surveying recent studies in the field. The potential and feasibility of graph-based deep learning for detecting anomalies in these networks are also explored. Finally, some remarks on modelling anomaly detection methods, using appropriate datasets for validation purposes and interpreting complex machine learning models are given.


Keywords: Internet of things; sensor networks; wireless networks; data security; machine learning

Free keywords: wireless sensor networks; anomaly detection; deep learning


Contributing organizations


Ministry reporting: Yes

Reporting Year: 2019

JUFO rating: 1


Last updated on 2020-09-07 at 11:47