On the race of worms and patches: modeling the spread of information in wireless sensor networks

Sayad Haghighi, Mohammad, Wen, Sheng, Xiang, Yang, Quinn, Barry and Zhou, Wanlei 2016, On the race of worms and patches: modeling the spread of information in wireless sensor networks, IEEE transactions on information forensics and security, vol. 11, no. 12, pp. 2854-2865, doi: 10.1109/TIFS.2016.2594130.

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Title On the race of worms and patches: modeling the spread of information in wireless sensor networks
Author(s) Sayad Haghighi, Mohammad
Wen, Sheng
Xiang, YangORCID iD for Xiang, Yang orcid.org/0000-0001-5252-0831
Quinn, Barry
Zhou, WanleiORCID iD for Zhou, Wanlei orcid.org/0000-0002-1680-2521
Journal name IEEE transactions on information forensics and security
Volume number 11
Issue number 12
Start page 2854
End page 2865
Total pages 12
Publisher IEEE
Place of publication Piscataway, N.J.
Publication date 2016-12
ISSN 1556-6013
Keyword(s) wireless sensor networks
worm propagation
epidemic theory
SI model
Science & Technology
Computer Science, Theory & Methods
Engineering, Electrical & Electronic
Computer Science
Summary Sensor networks are a branch of distributed ad hoc networks with a broad range of applications in surveillance and environment monitoring. In these networks, message exchanges are carried out in a multi-hop manner. Due to resource constraints, security professionals often use lightweight protocols, which do not provide adequate security. Even in the absence of constraints, designing a foolproof set of protocols and codes is almost impossible. This leaves the door open to the worms that take advantage of the vulnerabilities to propagate via exploiting the multi-hop message exchange mechanism. This issue has drawn the attention of security researchers recently. In this paper, we investigate the propagation pattern of information in wireless sensor networks based on an extended theory of epidemiology. We develop a geographical susceptible-infective model for this purpose and analytically derive the dynamics of information propagation. Compared with the previous models, ours is more realistic and is distinguished by two key factors that had been neglected before: 1) the proposed model does not purely rely on epidemic theory but rather binds it with geometrical and spatial constraints of real-world sensor networks and 2) it extends to also model the spread dynamics of conflicting information (e.g., a worm and its patch). We do extensive simulations to show the accuracy of our model and compare it with the previous ones. The findings show the common intuition that the infection source is the best location to start patching from, which is not necessarily right. We show that this depends on many factors, including the time it takes for the patch to be developed, worm/patch characteristics as well as the shape of the network.
Language eng
DOI 10.1109/TIFS.2016.2594130
Field of Research 080503 Networking and Communications
080303 Computer System Security
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30089221

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