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
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(1), 139; doi:10.3390/s17010139

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

School of Computer Science and Technology, Huaqiao University, Xiamen 361021, China
College of Information Technology, Deakin University, Melbourne, VIC 3125, Australia
School of Computer and Software, Nanjing University of Information Science & Technology, Nanjing 210044, China
These authors contributed equally to this work.
Author to whom correspondence should be addressed.
Academic Editor: Joel J. P. C. Rodrigues
Received: 12 November 2016 / Revised: 7 January 2017 / Accepted: 8 January 2017 / Published: 13 January 2017
(This article belongs to the Section Sensor Networks)
View Full-Text   |   Download PDF [4248 KB, uploaded 13 January 2017]   |  


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

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

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.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top