Practical Data Masking: How to address Development and QA teams' 7 most common data masking related reactions and concerns



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Bridging Strategy and Data Practical Data Masking: How to address Development and QA teams' 7 most common data masking related reactions and concerns Presented to: Northern California Oracle User s Group August 18 th, 2011

Who Needs to Mask What Data PII Data Employee Data Company Data Healthcare and Pharmaceutical - required to secure PHI per HIPAA Companies with customers in MA per MGL93H All organizations must follow their state privacy laws similar to Senate Bill No 1386 State of California Name Phone number, Email Address Street Address, Zip+4 Care of, Attn:... SSN or other national identifier Birth date and other dates Credit Card#, Bank Account# Comment fields Customer ID Account# Internal sequence key Healthcare and Pharmaceutical - required to secure PHI per HIPAA All organizations must follow their state privacy laws similar to Senate Bill No 1386 State of California Employee or Corporate ID Salary, Benefits HR status (termination, personnel issues) Family data Manager information Cost Center data Companies required to follow Gramm- Leach-Bliley Financial Services Modernization Act (1999) Companies required to follow Sarbanes- Oxley Act (2002) Multi-nationals - face requirements including: CANADA: Jan 2005 Personal Information Protection and Electronic Documents Act JAPAN: Apr 2005 Personal Information Protection Law FRANCE: Oct 2005 Computing and Liberties Act Vendor Data Security Identifiers CUSIP, ISIN, SEDOL Other Identifiers NAV, type of Security Name, Number, Symbol Activity Account balances, transactions, trade date Financials Price, quantity, legal fees, vendor payments Assets/holdings Comment fields Trade dates MASKING WHO, WHAT, WHY DMsuite 2011 Axis Technology, LLC. Confidential & Proprietary Information. 2

Practical Data Masking How to address Development and QA teams' 7 most common data masking related reactions and concerns: Post-Masking Stress Disorder A zero business value project You sunk my database! Oh yeah? Prove it. Who s going to clean up this mess? Just not in my backyard. Can t we all just get along? TYPICAL REACTIONS & CONCERNS 3

Post-Masking Stress Disorder 1. Helping your loved ones cope with the loss of their real production data Challenge We won t be able to test! The application won t work. I can t do my job like that... Solution Make target data look and act realistic. Let us show you just give us a sandbox, then check out the results before giving approval. Benefit Empower development teams in the process. Provide development teams with usable data. MASK INTELLIGENTLY 4

Post-Masking Stress Disorder 1. Helping your loved ones cope with the loss of their real production data MASK INTELLIGENTLY 5

You sunk my database! 2. When it comes to meeting application testing requirements, referential integrity is just the tip of the iceberg. Challenge These applications need to talk to each other even after they re masked. Solution Determine which systems: Must be masked in synch. Need to be masked first, then used to feed downstream applications. Identify data elements that must be preserved. Address interrelated fields. Select the best technique to mask each data element (context-dependent.) ALGORITHMS Benefit Applications work and interact seamlessly. 6

You sunk my database! 2. When it comes to meeting application testing requirements, referential integrity is just the tip of the iceberg. Framework Definition Features Examples Secure Lookup Segmented Mapping A proprietary algorithm, repeatable but unbreakable. Used to assign a realistic value from a pre-defined lookup values. While DMsuite comes with preconfigured secure lookups, a user can generate their own secure lookup values and easily import them into DMsuite. Create masked values by dividing target value into separate segments and masking each individually. A user can generate their own segmented mappings to mask with unique values consistently, and define values which need to be preserved, such as dashes, or semantically rich values. Irreversible Duplicates Intended Irreversible Can be defined to maintain uniqueness Names Addresses SSN Credit Card # Primary/Foreign Keys Account Numbers 7 ALGORITHMS

A zero business value project 3. How to make friends with testing teams and show ROI at the same time Challenge This is going to slow down and complicate my work. Solution Place more stringent controls on Production data. Employ automation wherever possible. Benefit A side benefit of an automated approach is that it creates greater efficiency in maintaining data masking as well as in other areas. With a better understanding of how the application and its data, bug- and break-fixing becomes faster and easier. BENEFITS OF AUTOMATION 8

A zero business value project 3. How to make friends with testing teams and show ROI at the same time Automated Analysis Effort No Automation Automation with DMsuite Data Masking Program Automated Change Capture BAU Automated Audit Safe Re-masking Periodic Audit Time BENEFITS OF AUTOMATION 9

Oh yeah? Prove it. 4. Showing results to ISOs, auditors, regulators, and sponsors Challenge We did masking last year, so we re all set. Solution Employ smart tools, process, automation and audit trails in the ongoing monitoring and periodic testing of masked environments. Benefit Make it easy to keep and show that a masked environment is still clean. PASSING AUDITS 10

Oh yeah? Prove it. 4. Showing results to ISOs, auditors, regulators, and sponsors PASSING AUDITS 11

Just not in my backyard. 5. Where data masking fits into your overall information security framework of controls Challenge We already don t just give anyone access Solution Keep in mind that Data Masking is not a onetime event; it s one of several tools in your Data Security Toolkit. Benefit Knowing when and where to employ data masking versus other data confidentiality controls (RBAC, lockdown, etc.) helps your organization avoid a slow-down in productivity. INFORMATION SECURITY CONTROLS 12

Just not in my backyard. PROD 5. Where data masking fits into your overall information security framework of controls PROD- Like LOCKDOWN No Persistent Access Controls Emergency Access Activity Monitoring Periodic Entitlements Reviews Secure Workspace, Disposal, and Data Erasure Strong Passwords and Segregation of Duties DATA MASKING UAT QA SIT DEV INFORMATION SECURITY CONTROLS 13

Who s going to clean up this mess? 6. Integrating data masking into the application development lifecycle Challenge How am I supposed to get my job done if I have to mask data at every step of the way? Solution Analyze each SDLC instance to determine the best potential in point for data masking. Benefit Data masking becomes part of the ongoing process, yet remains as behind-the-scenes as possible. SDLC INTEGRATION 14

Who s going to clean up this mess? 6. Integrating data masking into the application development lifecycle SDLC INTEGRATION 15

Can t we all just get along? 7. Options for a shared center of excellence architecture for data masking Challenge Sure this ll works for us, but our systems feed and receive data across businesses. Solution Build for at least a basic-level Center of Excellence for Data Masking. Benefit Achieve economies of scale by enabling your businesses to share knowledge about and resources for: Process Technology Organization CENTER OF EXCELLENCE 16

Can t we all just get along? 7. Options for a shared center of excellence architecture for data masking Center of Excellence Models CENTER OF EXCELLENCE 17

Axis Technology, LLC & Data Masking DMSuite - A robust, proprietary tool with data masking and self-service provisioning functionality. Straight out of the box, this software enables you to easily protect, provision and audit sensitive data. DATA PROTECTION OFFERINGS 18

Masks Applications Platforms Files Mainframe Verticals Retail Financial Services 19

Axis Technology, LLC Boston New York Dallas Bridging Strategy and Data 185 Devonshire Street Boston, MA 02110 www.axistechnologyllc.com THANK YOU.