David C. Frier discusses the importance of data protection and classification. He outlines common data protection threats like lost devices, disposal issues, and network exposure. While CEOs perceive effectiveness at 58%, other executives are lower at 48%. The most effective controls are seen as data loss prevention tools, while email filtering and backup encryption are seen as less effective. Frier advocates for classifying data into a taxonomy of 7 layers from kingdoms to species to appropriately focus protection efforts. This helps determine regulatory scope, prioritize coverage, and phase in programs.

1. It’s All About the Data!
David C. Frier, CISSP
Security Practice Lead
CIBER, Upstate NY
Oct. 21, 2010

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CIBER Profile
• CIBER is a $1Billion Global IT Services Company that
Builds, Integrates and Supports Business Applications
and IT Infrastructures for Business and Government
 Consistent growth and profitability since 1974
 More than 8,500 employees
 NYSE (CBR) - Headquartered in Denver
 85 Offices in 18 countries
 US and Offshore Development Centers
 Global IT Operations Centers – US & Europe
 Global practices supported by local resources
 Fortune 500 and mid-market leaders/challengers
 Focus on quality: ISO 9001, CPMM, SAS 70

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Frier Profile
• Frier is a less-than-$1Billion IT Professional who
Builds, Integrates and Supports Business Applications
and IT Infrastructures for Business and Government
 Consistent growth since 1957
 (first up then out)
 (DCF) - Headquartered in Rochester
 IT Operations first established in 1979
 IT Security, Operations, Architecture
 Project Management and Consulting
 Training and IT Evangelism
 CISSP, CRISC (pending)

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Outline
• What is in scope of Data Protection?
• What Threats exist?
• Who Cares?
• What is included in Data Protection?
• Is Data Protection Effective
• One approach for Data Classification

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– Regulated Data
• HIPAA
• PCI
• GLBA
– PII/SPI
• Under Safe Harbor
• Subject to Breach Disclosure laws
– Strategic Data
• IP
• Sales & Marketing Data
• Financial (SOX)
• M&A, Recruiting, other non-public plans
Data Protection – what is in scope

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• Lost or Stolen Devices
– Laptops and removable storage most common
• Disposal
– Incorrect disposal of disk and tape media
• Criminal Attacks
– Hacking more than physical theft
• Network Exposure
– Misconfigured web presence
– Email attachments
• Malicious Insiders
Threats to Data

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Who cares about Data Protection Programs?
Source: Business Case for Data Protection, Ponemon Institute, July 2009

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• Data Loss Prevention-
Network
• Data Loss Prevention-
Endpoint
• Data Loss Prevention- Storage
• Content Discovery (Process)
• Email Filtering
• Database Activity Monitoring
• Full Drive Encryption
• USB/Portable Media
Encryption or Device Control
• Enterprise Digital Rights
Management
• Database Encryption
• Application Encryption
• Web Application Firewall
• Backup Tape Encryption
• Entitlement Management
• Access Management
• Data Masking
• Network Segregation
• Server/Endpoint Hardening
Enterprise Data Protection – what is included

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• Perceived Effectiveness ¹
– CEOs: 58%
– Other C-Levels: 48%
• Which Controls are Most Effective²
Data Loss Prevention- Network
Data Loss Prevention- Endpoint
Data Loss Prevention- Storage
Content Discovery (Process)
Email Filtering
Are Corporate Data Protection Programs Effective?
2 – Source: Securosis 2010 Data Security Survey, Securosis, LLC, … 2010
1 – Source: Business Case for Data Protection, Ponemon Institute, July 2009

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• Which Controls are Least Effective?
Email Filtering
USB/Portable Media Encryption or Device Control
Database Activity Monitoring
Backup Tape Encryption
Content Discovery (Process)
Notice anything odd?
Why Are Corporate Data Protection Programs Effective?
Source: Securosis 2010 Data Security Survey, Securosis, LLC, … 2010

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Do you know what
you are charged to protect?

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Who recognizes this?
Kings play chess on finely grained sand

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Did you take zoology in school?
Kings play chess on finely grained sand
• Kingdom
• Phylum
• Class
• Order
• Family
• Genus
• Species

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• Use a Taxonomy
• From Kingdoms, the highest level, down to individual
reports and documents
• Seven layers may seem like a lot
– …but it’s easy to find pockets where you need more
Data Classification

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• Start with “Public” and “Non-Public”
• You might add a third for customer-privileged
information
• Most Data protection effort will focus on Non-Public
The point of the taxonomy is to successively sharpen the
focus of the enterprise data protection efforts
Data Classification -- Kingdoms

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• This is a good layer for your data owner organizations
– Yes: All data must have an owner.
– Owners make the decisions about what level of protection
is needed
– Typically, data owners are the groups that own the
processes that create/update/delete the data
• From here down you will see categories repeated
– This is the way to express the matrix nature of some of
these designations across the top-down hierarchy
Data Classification -- Phyla

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Data Classification -- Classes
• At the Class level you can apply the levels-of-
sensitivity classifications
– Confidential
– Sensitive
– “Company only”
These are suggestions only… the important thing is to be
consistent across all the data with what you do at a given
level

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• With Order, start to divide up the data into groups of
related business processes
– Example: within the HR phylum,
• Payroll
• Benefits
• Performance Mgt.
• Recruiting
– Each of these may be in different classes for sensitivity
– Class designations will often repeat across phyla but that’s
OK
Data Classification -- Orders

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• For Family, get to the application or system level
– For example, within the Benefits order
• One app manages Health Care
• Another manages PTO
• Another for Tuition Reimbursement
• etc.
– It is also likely that this isolates specific business processes
– “Applications” in this context may be modules within larger
enterprise systems
Data Classification -- Families

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• Genus is a particular data type
– Reports
– Databases
– Feed files
• Species is instances of those types
– “The weekly payroll register”
– “The monthly healthcare claims report”
Data Classification – Genus & Species

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Let’s look at that payroll report
• Kingdom – Non-public
• Phylum – HR
• Class – Confidential
• Order – Payroll
• Family – ADP interface
• Genus – Reports
• Species – Payroll report

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• Classification and handling decisions may be made
wherever appropriate
– For example, a single massive database may power an
enterprise HRIS that is classified at the Order level
– And that database might not be safe to have try to support
multiple levels of security, so you decide to take the “worst
case” approach.
• You may not need all the levels
– But if you give yourself the room you will get this done to
enough detail to make informed decisions
Data Classification – Put it to use

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• Determine Regulatory Scope
• Prioritize Coverage
• Phase-in Programs
• Get below-C Mgt. Buy-In
• Communicate why you are acting to protect this and
not that (yet)
Data Classification – Put it to use

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Remember!
It’s all about the data!

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• Ponemon Reports
– http://www.ponemon.org/data-security
• Securosis Survey
– http://www.imperva.com/resources/analyst.html
• CIBER
– http://www.ciber.com/
• Frier
– dfrier@ciber.com
More Resources