Location

Hilton Waikoloa Village, Hawaii

Event Website

http://www.hicss.hawaii.edu

Start Date

1-4-2017

End Date

1-7-2017

Description

A large number of mission critical applications ranging from disaster management to smart city are built on the Internet of Things (IoT) platform by deploying a number of smart sensors in a heterogeneous environment. The key requirements of such applications are the need of near real-time stream data processing in large scale sensing networks. This trend gives birth of an area called big data stream. One of the key problems in big data stream is to ensure the end-to-end security. To address this challenge, we proposed Dynamic Prime Number Based Security Verification (DPBSV) and Dynamic Key Length Based Security Framework (DLSeF) methods for big data streams based on the shared key derived from synchronized prime numbers in our earlier works. One of the major shortcomings of these methods is that they assume synchronization of the shared key. However, the assumption does not hold when the communication between Data Stream Manager (DSM) and sensing devices is broken. To address this problem, this paper proposes an adaptive technique to synchronize the shared key without communication between sensing devices and DSM, where sensing devices obtain the shared key re-initialization properties from its neighbours. Theoretical analyses and experimental results show that the proposed technique can be integrated with our DPBSV and DLSeF methods without degrading the performance and efficiency. We observed that the proposed synchronization method also strengthens the security of the models.

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Jan 4th, 12:00 AM Jan 7th, 12:00 AM

A Synchronized Shared Key Generation Method for Maintaining End-to-End Security of Big Data Streams

Hilton Waikoloa Village, Hawaii

A large number of mission critical applications ranging from disaster management to smart city are built on the Internet of Things (IoT) platform by deploying a number of smart sensors in a heterogeneous environment. The key requirements of such applications are the need of near real-time stream data processing in large scale sensing networks. This trend gives birth of an area called big data stream. One of the key problems in big data stream is to ensure the end-to-end security. To address this challenge, we proposed Dynamic Prime Number Based Security Verification (DPBSV) and Dynamic Key Length Based Security Framework (DLSeF) methods for big data streams based on the shared key derived from synchronized prime numbers in our earlier works. One of the major shortcomings of these methods is that they assume synchronization of the shared key. However, the assumption does not hold when the communication between Data Stream Manager (DSM) and sensing devices is broken. To address this problem, this paper proposes an adaptive technique to synchronize the shared key without communication between sensing devices and DSM, where sensing devices obtain the shared key re-initialization properties from its neighbours. Theoretical analyses and experimental results show that the proposed technique can be integrated with our DPBSV and DLSeF methods without degrading the performance and efficiency. We observed that the proposed synchronization method also strengthens the security of the models.

http://aisel.aisnet.org/hicss-50/st/cyber-of-things/2