Secure Mobile Payment Scheme Using Machine Learning

The paper examines portable installment systems' expanding acknowledgment and the security imperfections that come with them. Whereas protecting client security and comfort, it highlights how direly security measures must be moved forward. The consider puts out a intensive arrange that fortifies security forms with machine learning, permitting for the quick recognizable proof and relief of dangers. The Arbitrary Woodland classifier is a principal component of this procedure since of its strength and capacity to oversee complex information intelligent. The objective of the inquire about is to accomplish a adjust between effective defense against creating assault vectors and consistent client encounter by combining progressed machine learning methods, such as Irregular Timberland, with current security systems. Careful testing is done to evaluate this approach's viability versus.

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Publication Details

Published
2024-12-13
DOI
https://doi.org/10.1109/ictbig64922.2024.10911321
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
Field-Weighted Citation Impact
0.00
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article

Secure Mobile Payment Scheme Using Machine Learning

D. Srinivasa Rao, N. Geetha
Privacy-Preserving Technologies in Data
article

Secure Mobile Payment Scheme Using Machine Learning

D. Srinivasa Rao, N. Geetha
article en

Abstract

The paper examines portable installment systems' expanding acknowledgment and the security imperfections that come with them. Whereas protecting client security and comfort, it highlights how direly security measures must be moved forward. The consider puts out a intensive arrange that fortifies security forms with machine learning, permitting for the quick recognizable proof and relief of dangers. The Arbitrary Woodland classifier is a principal component of this procedure since of its strength and capacity to oversee complex information intelligent. The objective of the inquire about is to accomplish a adjust between effective defense against creating assault vectors and consistent client encounter by combining progressed machine learning methods, such as Irregular Timberland, with current security systems. Careful testing is done to evaluate this approach's viability versus.

Openalex Percentile: Top 74%
Privacy-Preserving Technologies in Data
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