Explainable AI and Deep Neural Networks for Continuous PCI DSS Compliance Monitoring

Ensuring constant PCI DSS compliance isessential but not easy when dealing with PCI DSS-sensitivepayment card information. This paper looks into XAI andDNNs to examine their possibilities of implementing andimproving PCI DSS compliance check automation. XAImakes a model explain itself, making it easy for complianceofficers to address non-compliance when identified by themodel. For their part, DNNs can sift through large amounts ofsecurity data to look for anomalies, determine theeffectiveness of the access control measures, verify theimplementation of encryption for data, and monitor theeffectiveness of controls of vulnerabilities. Applying thesehigh-level AI methodologies can allow organizations to gainbetter, even real-time, control over compliance, thussignificantly reducing the probabilities of securityinfringements and enhancing data protection measures ingeneral. Not only does it build up compliance capabilities, butit also provides scalable and preventive solutions in reactionto the emerging threats in the cyber security domain.