%0 Conference Proceedings
%T Implementing a Broadcast Storm Attack on a Mission-Critical Wireless Sensor Network
%+ National Research University of Information Technologies, Mechanics and Optics [St. Petersburg] (ITMO)
%+ Tampere University of Technology [Tampere] (TUT)
%+ Brno University of Technology  [Brno] (BUT)
%A Krivtsova, Irina
%A Lebedev, Ilya
%A Sukhoparov, Mikhail
%A Bazhayev, Nurzhan
%A Zikratov, Igor
%A Ometov, Aleksandr
%A Andreev, Sergey
%A Masek, Pavel
%A Fujdiak, Radek
%A Hosek, Jiri
%Z Part 7: Wireless Sensor Networks
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 14th International Conference on Wired/Wireless Internet Communication (WWIC)
%C Thessaloniki, Greece
%Y Lefteris Mamatas
%Y Panagiotis Papadimitriou
%Y Ibrahim Matta
%Y Yevgeni Koucheryavy
%3 Wired/Wireless Internet Communications
%V LNCS-9674
%P 297-308
%8 2016-05-25
%D 2016
%R 10.1007/978-3-319-33936-8_23
%K Information security
%K Ad hoc networks
%K Multi-agent systems
%K Vulnerability
%K Device availability
%K Prototyping
%Z Computer Science [cs]
%Z Computer Science [cs]/Networking and Internet Architecture [cs.NI]Conference papers
%X In this work, we emphasize the practical importance of mission-critical wireless sensor networks (WSNs) for structural health monitoring of industrial constructions. Due to its isolated and ad hoc nature, this type of WSN deployments is susceptible to a variety of malicious attacks that may disrupt the underlying crucial systems. Along these lines, we review and implement one such attack, named a broadcast storm, where an attacker is attempting to flood the network by sending numerous broadcast packets. Accordingly, we assemble a live prototype of said scenario with real-world WSN equipment, as well as measure the key operational parameters of the WSN under attack, including packet transmission delays and the corresponding loss ratios. We further develop a simple supportive mathematical model based on widely-adopted methods of queuing theory. It allows for accurate performance assessment as well as for predicting the expected system performance, which has been verified with statistical methods.
%G English
%Z TC 6
%Z WG 6.2
%2 https://inria.hal.science/hal-01434859/document
%2 https://inria.hal.science/hal-01434859/file/417220_1_En_23_Chapter.pdf
%L hal-01434859
%U https://inria.hal.science/hal-01434859
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC6
%~ IFIP-LNCS-9674
%~ IFIP-WG6-2
%~ IFIP-WWIC