Next Article in Journal
Cluster-Based Maximum Consensus Time Synchronization for Industrial Wireless Sensor Networks
Previous Article in Journal
A Mechanism for Reliable Mobility Management for Internet of Things Using CoAP
Open AccessArticle

Propagation Modeling and Defending of a Mobile Sensor Worm in Wireless Sensor and Actuator Networks

by 1,*,†, 1,†, 2, 1, 1, 1 and 3
1
School of Computer Science and Technology, Huaqiao University, Xiamen 361021, China
2
College of Information Technology, Deakin University, Melbourne, VIC 3125, Australia
3
School of Computer and Software, Nanjing University of Information Science & Technology, Nanjing 210044, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Joel J. P. C. Rodrigues
Sensors 2017, 17(1), 139; https://doi.org/10.3390/s17010139
Received: 12 November 2016 / Revised: 7 January 2017 / Accepted: 8 January 2017 / Published: 13 January 2017
(This article belongs to the Section Sensor Networks)
WSANs (Wireless Sensor and Actuator Networks) are derived from traditional wireless sensor networks by introducing mobile actuator elements. Previous studies indicated that mobile actuators can improve network performance in terms of data collection, energy supplementation, etc. However, according to our experimental simulations, the actuator’s mobility also causes the sensor worm to spread faster if an attacker launches worm attacks on an actuator and compromises it successfully. Traditional worm propagation models and defense strategies did not consider the diffusion with a mobile worm carrier. To address this new problem, we first propose a microscopic mathematical model to describe the propagation dynamics of the sensor worm. Then, a two-step local defending strategy (LDS) with a mobile patcher (a mobile element which can distribute patches) is designed to recover the network. In LDS, all recovering operations are only taken in a restricted region to minimize the cost. Extensive experimental results demonstrate that our model estimations are rather accurate and consistent with the actual spreading scenario of the mobile sensor worm. Moreover, on average, the LDS outperforms other algorithms by approximately 50% in terms of the cost. View Full-Text
Keywords: WSANs (wireless sensor and actuator networks); mobile sensor worm; modeling; patch; mobile patcher WSANs (wireless sensor and actuator networks); mobile sensor worm; modeling; patch; mobile patcher
Show Figures

Figure 1

MDPI and ACS Style

Wang, T.; Wu, Q.; Wen, S.; Cai, Y.; Tian, H.; Chen, Y.; Wang, B. Propagation Modeling and Defending of a Mobile Sensor Worm in Wireless Sensor and Actuator Networks. Sensors 2017, 17, 139.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map

1
Back to TopTop