Privacy Preservation of Sink Node Location in Wireless Sensor Network Using RFSN-RSA

Privacy Preservation of Sink Node Location in Wireless Sensor Network Using RFSN-RSA

Kolli V. Krishna KishorePondugala Sudheer Kumar Dondeti Venketasulu

Department of CSE, VFSTR, Vadlamudi, AP 522213, India

Corresponding Author Email: 
kishorekvk_1@yahoo.com
Page: 
57-63
|
DOI: 
https://doi.org/10.18280/ama_b.610201
Received: 
8 April 2018
|
Accepted: 
12 June 2018
|
Published: 
30 June 2018
| Citation

OPEN ACCESS

Abstract: 

Sink Node location privacy in sensor networks deployed in Industrial Internet of Things (IIOT) is one of the challenging tasks because of data security and protection.  In industrial sensor networks, sensor nodes transfer data packets from a source node to sink node (base station) by using the multi-hop technique.  Based on the nature of the sensor network, adversaries may easily track the sink node location by traffic analysis. There are many approaches to overcome this problem. In this paper, we proposed an approach to preserve the privacy of the sink node in addition to secured data transmission from adversaries attacks.  In our work, random fake sink node (RFSN) approach is used to mislead the adversary.  After forming the clusters, and cluster heads  (CH), one of the cluster head will be selected randomly as fake sink node (FSN), and all other CHs send fake data packets to this FSN to mislead adversary.  Fake sink nodes are changed dynamically at intervals to make it difficult for an adversary to distinguish between FSN and original sink node. The simulation results show the privacy of the sink node location is preserved from the adversaries with an elongated lifetime of sensor nodes. The simulation result also proved that the proposed approach with RSA algorithm has provided more security with low packet loss.

Keywords: 

IIOT, wireless sensor network, privacy preservation, adversaries attacks, Random fake sink node, RFSN-RSA, cluster head

1. Introduction
2. Literature Survey
3. Methodology
4. Simulation Results
5. Conclusion
  References

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