Abstract:

The PCI DSS, or Payment Card Industry Data Security Standard in full, is an essential reference for processing card holder data securely. Compliance with these standards, nonetheless, is challenging given the compressed and large amount of data that currently characterizes most payment systems. This paper focuses on understanding the use of scalable neural network models for automating PCI DSS compliance. The work explores simulation models, real processes, and solutions that help avoid or minimize compliance problems. The summary includes tables and graphs to support the main quantitative conclusions. A thorough analysis of the impediments and advantages focuses on the realities of the implementation process. Based on the findings presented in this work, some practical suggestions for organizations interested in employing large neural networks to achieve compliance with PCI DSS requirements are provided.

Description:

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