How to Secure AI Infrastructure & Data in JD Edwards – Complete Guide

In this episode of "Not Your Grandpa's JD Edwards," host Nate Bushfield sits down with Brian Connor, Director of JD Edwards Security at ERP Suites, to explore essential strategies for securing sensitive data, particularly when leveraging AI technologies. Brian shares insights on data encryption, identity management, security assessments, and practical methods to protect your infrastructure from cyber threats and malicious attacks. By the end of this discussion, you'll understand the critical steps needed to proactively safeguard your organization’s data and maintain customer trust.

Table of Contents

1. Introduction: The Importance of Data Security

2. Risks of Compromised Sensitive Data

3. Identifying Vulnerabilities

4. Steps to Secure AI Infrastructure

5. Understanding Vendor and Customer Security Roles

6. Boundary Protection and Malicious Code Defense

7. Practical Examples of Effective Security Implementation

8. The Role of Vulnerability Scans and Assessments

9. Identity and Access Management Essentials

10. Next Steps: Improving Your Security

Transcript with Headers

Introduction: The Importance of Data Security

Are you concerned about how securely your sensitive data is managed, especially when leveraging AI? Wondering if your business is truly protected against vulnerabilities and cyber threats?

Today, I'm joined by Brian Connor from ERP Suites to outline essential strategies for encryption, security assessments, and protecting your AI infrastructure against malicious attacks.

Brian, welcome—how are you doing today?

Doing fantastic, Nate. It's a beautiful day, looking forward to the weekend.

Great to have you. Could you tell our listeners about your background and how you got into data security?

I've been working with JD Edwards for about 30 years, the last 15 focused on security and compliance, naturally transitioning into data security and cloud security.

Risks of Compromised Sensitive Data

Why should businesses be concerned about data security, especially when using AI?

Data is the lifeblood of your company—without it, you have nothing. Cybercriminals specifically target data, making data security a critical focus not just with AI but across your entire organization.

What risks are businesses exposed to without robust security measures?

There's the obvious cost of remediation, but the most damaging impact is to your reputation. If you lose customer trust, it’s extremely difficult to regain.

Identifying Vulnerabilities

How can organizations recognize vulnerabilities in their current data and AI practices?

Regular security assessments and continuous monitoring are key. Companies often think they've done everything right until they discover otherwise. Regular assessments help identify gaps before they become problems.

Steps to Secure AI Infrastructure

Once vulnerabilities are identified, what are the first steps to secure your AI infrastructure?

The best defense is a good offense. Automate detection and responses to vulnerabilities. Leverage solutions like OCI to handle critical threats instantly rather than waiting for manual intervention.

Understanding Vendor and Customer Security Roles

Could you break down the roles of vendors and customers in maintaining effective data encryption?

Vendors manage encryption (data in transit and at rest), key management, and secure communications. Customers handle data classification, retention policies, compliance (GDPR, HIPAA), and auditing.

Also, be aware of older data—if it's no longer needed, archive it. Old data can become a liability if left unmanaged.

Boundary Protection and Malicious Code Defense

Why is boundary protection and malicious code defense critical for businesses leveraging AI?

Boundaries used to be clear—now they are fluid, especially with cloud-based AI services. You need to define policies around identity and access management, security lists, and network security groups to maintain clear boundaries.

Practical Examples of Effective Security Implementation

Could you share practical examples of businesses that have successfully implemented robust security for AI applications?

Using OCI, data encryption is default and cannot be disabled. ERP Suites employs CIS-certified secure "landing zones" for customers, deploying fully secured environments with pre-defined security configurations (network security groups, identity management, etc.).

The Role of Vulnerability Scans and Assessments

How do vulnerability scans and security assessments contribute to ongoing data protection?

Vulnerabilities evolve constantly. Continuous scanning helps identify anomalies and threats in real time, while regular assessments help detect patterns and proactively mitigate future risks.

Identity and Access Management Essentials

Could you elaborate on identity and access management (IAM) and how it secures AI access?

IAM is foundational—if you get this wrong, you're vulnerable. Implement federated access control to automate user account creation securely, use granular security lists, and clearly segregate access privileges. Infrastructure teams shouldn't modify identity policies, and vice versa. This strict control maintains security integrity.

Next Steps: Improving Your Security

If today's discussion has increased your awareness and you're ready to strengthen your organization's security posture, reach out to ERP Suites. Connect with Brian Connor to schedule a security assessment and begin safeguarding your data effectively. Visit erpsuites.com to take the first step toward robust protection.

That's all for this episode of "Not Your Grandpa's JD Edwards." Big thanks to Brian Connor for his invaluable insights into data security. If you found this helpful, subscribe, leave a review, and share with colleagues dedicated to securing their sensitive data.

Stay secure, stay vigilant, and keep improving.