Improving Data Integrity in Oracle E-Business Suite: An AI-Powered Cybersecurity Framework for Finding Threats and Managing Compliance

In order to ensure that enterprise resource planning (ERP) systems continue to maintain a high level of data security and that they continue to meet the criteria, cybersecurity specialists should periodically monitor these systems. It is widely acknowledged that the Oracle E-corporate Suite (EBS) is among the most widely used enterprise resource planning (ERP) products that have ever been developed. It’s used by a lot of companies all over the world already. Client information, supply chain management systems, and financial transactions are all examples of the private firm data that it is responsible for documenting and being responsible for keeping track of. The goal of this design is to create a more secure environment for data, identify potential vulnerabilities in security, and facilitate compliance management programs in meeting their criteria in a more straightforward manner. AI solutions like deep learning models, anomaly detection, and smart auditing help the system detect and prevent these errors. The provided system uses multi-layer security analytics technology to monitor access and transaction records in real time. This task must be done to keep the model working. Machine learning algorithms look for unusual data patterns to do this. These unusual events may help us discover insider threats, illicit access, and data alteration. Natural Language Processing (NLP) helps the system find contextual risk signs that other monitoring systems may miss, making log analysis easier. Through the use of experimental validation, it has been demonstrated that the framework makes the data significantly more reliable, reduces the number of false alarms, and provides valuable information to the management of the system. It is a clever and valuable addition to Oracle EBS’s security system since it changes dependent on how users behave and how different cyber threats are different. This makes it a flexible and effective addition. This is an addition that is both practical and logical. Finding a connection between classic ERP security measures and new defense mechanisms based on artificial intelligence is the objective of this research. These defense mechanisms will protect data and ensure that the legislation is followed accordingly.