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Secret-Sharing Approach for Detecting Compromised Mobile Sink in Unattended Wireless Sensor Networks

  • Xiangyi Chen
  • Liangmin Wang
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 747)

Abstract

In unattended wireless sensor networks (UWSNs), static sensor nodes monitor environment, store sensing data in memory temporally. Mobile sink patrols and collects the sensors’ data itinerantly. Mobile sink is granted with more permissions than static sensor nodes, rendering it more attractive to the adversary. By compromising the mobile sinks, the adversary can not only seek the sensing data, but it also can steel all kinds of keys and access permissions, which may be abused to undermine other benign sensor nodes, even worse to upset the whole network. Currently, many related works focus on key management, permission management to restrict the compromised mobile sink or authentication to guarantee data reliability. However, the issue of compromised mobile sinks attracts little attention, and gradually become one obstacle to the application of UWSNs.

In this paper, we proposed a secret-sharing method for detecting compromised mobile sink in UWSNs. Before the sensing data are collected by the mobile sink, every sensor node splits the digest of its data into shares by using a polynomial secret sharing algorithm, and dispatches these secret shares to randomly chosen neighbor nodes, which thereafter send to the base-station through different routes. After enough shares are gathered, the base-station recovers the original data digest, which will be used to validate the sensing data submitted by the mobile sink. If the validation fails, it reveals a compromised mobile sink. Theoretical analysis and evaluation indicate the effectiveness and efficiency of our method. Also, we proposed two types of attacking model of the mobile adversary, and obtained the respective detection probability.

Keywords

Detecting Compromised mobile sink Secret sharing Unattended wireless sensor networks 

Notes

Acknowledgment

This work is supported by the National Natural Science Foundation of China under Grant No. 61272074 and No. U1405255, the Key Research & Development Project of Jiangsu Province under Grant No. BE2015136, and the Industrial Science and Technology Foundation of Zhenjiang City under Grant No. GY2013030.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.School of Computer Science and Telecommunication EngineeringJiangsu UniversityZhenjiangChina

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