Text-Mining Research Group

On the Energy Consumption of Quantum-resistant Cryptographic Software Implementations Suitable for Wireless Sensor Networks

For an effective protection of the communication in Wireless Sensor Networks (WSN) facing e.g. threats by quantum computers in the near future, it is necessary to examine the applicability of quantum-resistant mechanisms in this field. It is the aim of this article to survey possible candidate schemes utilizable on sensor nodes and to compare the energy consumption of a selection of freely-available software implementations using a WSN-ready Texas Instruments CC1350 LaunchPad ARM® Cortex®-M3 microcontroller board.

This is a preprint version of the article.

Keywords: wireless sensor networks, post-quantum cryptography, energy consumption

Year: 2019

Download:  Full text [642 kB]

Michael Heigl

E-mail: heigl@kiv.zcu.cz

Michael is currently working as a research associate at the institute ProtectIT at the Deggendorf Institute of Technology and holds a Ph.D. degree from the University of West Bohemia for his dissertation on machine learning enhanced network-based anomaly detection. He is specialized in improving outlier detection methods for streaming data applications.

Laurin Doerr

Martin Schramm

Dalibor Fiala

Phone: +420 377 63 2429
E-mail: dalfia@kiv.zcu.cz
WWW: http://www.kiv.zcu.cz/~dalfia/

Dalibor is the research group coordinator and an associate professor at the Department of Computer Science and Engineering at the University of West Bohemia in Pilsen, Czech Republic. He is interested in data mining, web mining, information retrieval, informetrics, and information science.

Data Mining for Computer Networks Security
Authors:	Michael Heigl, Laurin Doerr, Dalibor Fiala
Desc.:	Novel data mining methods for the enhancement of computer networks security using advanced outlier detection techniques on streaming data are investigated.