A Novel Method to Solve Real Time Security Issues in Software Industry Using Advanced Cryptographic Techniques

In recent times, the utility and privacy are trade-off factors with the performance of one factor tends to sacrifice the other. Therefore, the dataset cannot be published without privacy. It is henceforth crucial to maintain an equilibrium between the utility and privacy of data. In this paper, a no...

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Published inScientific programming Vol. 2021; pp. 1 - 9
Main Authors Gobinathan, B., Mukunthan, M. A., Surendran, S., Somasundaram, K., Moeed, Syed Abdul, Niranjan, P., Gouthami, V., Ashmitha, G., Mohammad, Gouse Baig, Shanmuganathan, V. K., Natarajan, Yuvaraj, Srihari, K., Sundramurthy, Venkatesa Prabhu
Format Journal Article
LanguageEnglish
Published New York Hindawi 28.12.2021
John Wiley & Sons, Inc
Subjects
Algorithms
Assaults
Clustering
Cryptography
Data integrity
Data mining
Datasets
Heuristic methods
Manufacturing
Privacy
Tradeoffs
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Abstract In recent times, the utility and privacy are trade-off factors with the performance of one factor tends to sacrifice the other. Therefore, the dataset cannot be published without privacy. It is henceforth crucial to maintain an equilibrium between the utility and privacy of data. In this paper, a novel technique on trade-off between the utility and privacy is developed, where the former is developed with a metaheuristic algorithm and the latter is developed using a cryptographic model. The utility is carried out with the process of clustering, and the privacy model encrypts and decrypts the model. At first, the input datasets are clustered, and after clustering, the privacy of data is maintained. The simulation is conducted on the manufacturing datasets over various existing models. The results show that the proposed model shows improved clustering accuracy and data privacy than the existing models. The evaluation with the proposed model shows a trade-off privacy preservation and utility clustering in smart manufacturing datasets.
AbstractList In recent times, the utility and privacy are trade-off factors with the performance of one factor tends to sacrifice the other. Therefore, the dataset cannot be published without privacy. It is henceforth crucial to maintain an equilibrium between the utility and privacy of data. In this paper, a novel technique on trade-off between the utility and privacy is developed, where the former is developed with a metaheuristic algorithm and the latter is developed using a cryptographic model. The utility is carried out with the process of clustering, and the privacy model encrypts and decrypts the model. At first, the input datasets are clustered, and after clustering, the privacy of data is maintained. The simulation is conducted on the manufacturing datasets over various existing models. The results show that the proposed model shows improved clustering accuracy and data privacy than the existing models. The evaluation with the proposed model shows a trade-off privacy preservation and utility clustering in smart manufacturing datasets.
Author Sundramurthy, Venkatesa Prabhu
Surendran, S.
Niranjan, P.
Mukunthan, M. A.
Somasundaram, K.
Gobinathan, B.
Ashmitha, G.
Moeed, Syed Abdul
Srihari, K.
Natarajan, Yuvaraj
Mohammad, Gouse Baig
Shanmuganathan, V. K.
Gouthami, V.
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Copyright Copyright © 2021 B. Gobinathan et al.
Copyright © 2021 B. Gobinathan et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
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SubjectTerms Algorithms
Assaults
Clustering
Cryptography
Data integrity
Data mining
Datasets
Heuristic methods
Manufacturing
Privacy
Tradeoffs
Title A Novel Method to Solve Real Time Security Issues in Software Industry Using Advanced Cryptographic Techniques
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