A Hybrid Technique for Enhancing Data Integrity in Big Data Transmission Environment

Bhattacharjee, S. and Ab Rahim, L.B. and Zakaria, M.N.B. and Ab Aziz, I.B. (2018) A Hybrid Technique for Enhancing Data Integrity in Big Data Transmission Environment. In: UNSPECIFIED.

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Abstract

Data loss primarily occurs due to huge data size, channel limitations, transmission errors and distinct security attacks. A number of individual or combined efforts have been made to control data size and channel capacity using distinct data compressions, protect numerous security hazards and transportation errors using diverse cryptographies as well as error control techniques. However, the current literature fails to address all these issues mutually with desired time and space efficiencies. Therefore, this research work suggests a hybrid technique which comprises an innovative pattern generation and a new error restraint technique for handling any numbers of isolated or incessant transmission errors. The pattern strings are generated in this mechanism by using a newly designed pattern table. A distinctive lossless compression technique is further incorporated within it to control data size and integrity. Experimented results indicate that the planned hybrid technique is competent to decrease the data loss and errors in compare to other existing technique by offering low Information Loss percentage and high SNR. The obtained results also display its time and space efficiencies by producing higher Compression Percentage and Throughput. © 2018 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 0; Conference of 4th International Conference on Computer and Information Sciences, ICCOINS 2018 ; Conference Date: 13 August 2018 Through 14 August 2018; Conference Code:141665
Uncontrolled Keywords: Channel capacity; Efficiency; Errors; Signal to noise ratio, Data integrity; Error control techniques; High SNR; Lossless compression techniques; Pattern Generation; pattern table; Space efficiencies; Transmission error, Big data
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 16:36
Last Modified: 09 Nov 2023 16:36
URI: https://khub.utp.edu.my/scholars/id/eprint/9850

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