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End-to-end security framework for big sensing data streams

Lookup NU author(s): Dr Deepak Puthal, Professor Raj Ranjan

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Abstract

© 2017 by Taylor & Francis Group, LLC. Big data streaming has become an important paradigm for real-time processing of massive continuous data flows in large-scale sensing networks. While dealing with big sensing data streams from Internet of Things (IoT), a data stream manager (DSM) must always verify the authenticity, integrity, and confidentiality of the data to ensure end-to-end security as the medium of communication is wireless and untrusted. Malicious attackers could access and modify the data at any time/place from source to cloud data center. Existing technologies for data security verification are not suitable for data-streaming applications, as the verification should be performed in real time and which introduces a delay in the data stream. In this chapter, we will propose a Dynamic Prime-Number- Based Security Verification (DPBSV) framework for big data streams. Our framework is based on a common shared key that is updated dynamically by generating synchronized prime numbers. The common shared key updates at both ends, that is, source-sensing devices and DSM, without further communication after handshaking. Theoretical analyses and experimental results of our DPBSV framework show that it can significantly improve the efficiency of the verification process by reducing the time and utilizing a smaller buffer size in DSM.We have experimented the proposed scheme in a simulated environment and demonstrated the feasibility of the approach. We observed that the proposed scheme not only reduces the verification time or buffer size in DSM, but also strengthens the security of the data by constantly changing the shared keys.


Publication metadata

Author(s): Puthal D, Nepal S, Ranjan R, Chen J

Editor(s): Kuan-Ching Li, Hai Jiang, Albert Y. Zomaya

Publication type: Book Chapter

Publication status: Published

Book Title: Big Data Management and Processing

Year: 2017

Pages: 263-278

Print publication date: 19/05/2017

Online publication date: 19/05/2017

Acceptance date: 02/04/2016

Publisher: CRC Press

Place Published: New York

URL: https://doi.org/10.1201/9781315154008

DOI: 10.1201/9781315154008

Library holdings: Search Newcastle University Library for this item

ISBN: 9781498768085


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