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Locating Unmanaged but Regulated Data
on z Systems: CA Data Content Discovery
Mary Ann Furno
Mainframe
CA Technologies
Director, Software Engineering
MFX25S
2 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
For Informational Purposes Only
Terms of this Presentation
© 2015 CA. All rights reserved. All trademarks referenced herein belong to their respective companies. The presentation provided at CA
World 2015 is intended for information purposes only and does not form any type of warranty. Some of the specific slides with customer
references relate to customer's specific use and experience of CA products and solutions so actual results may vary.
Certain information in this presentation may outline CA’s general product direction. This presentation shall not serve to (i) affect the rights
and/or obligations of CA or its licensees under any existing or future license agreement or services agreement relating to any CA software
product; or (ii) amend any product documentation or specifications for any CA software product. This presentation is based on current
information and resource allocations as of November 18, 2015, and is subject to change or withdrawal by CA at any time without notice. The
development, release and timing of any features or functionality described in this presentation remain at CA’s sole discretion.
Notwithstanding anything in this presentation to the contrary, upon the general availability of any future CA product release referenced in
this presentation, CA may make such release available to new licensees in the form of a regularly scheduled major product release. Such
release may be made available to licensees of the product who are active subscribers to CA maintenance and support, on a when and if-
available basis. The information in this presentation is not deemed to be incorporated into any contract.
3 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
Abstract
CA Data Content Discovery helps you identify
data exposure risks on z Systems by scanning
through the mainframe data infrastructure.
By discovering where the data is located,
classifying the data to determine sensitivity
level, and providing comprehensive reporting
on the scan results, data can be adequately
protected and exposure risks can be mitigated.
Mary Ann
Furno
CA Technologies
Director, Software
Engineering
4 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
Agenda
CISOS, REGULATED DATA, AND THE MAINFRAME
SENSITIVE DATA DEFINED
DATA CONTENT DISCOVERY ON THE MAINFRAME
DATA CONTENT DISCOVERY ROADMAP
1
2
3
4
CISOs, Regulated Data,
and the Mainframe
6 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
The Mainframe has never been hacked!
Mainframe data stays on the
mainframe; so it is safe!
Data is fluid in today’s world.
Data analytics; cloud
Marriage of MF data and non MF data
Mainframe is well understood and
covered under three lines of risk
control– Operational, Compliance and
Internal audit
The Current State
REALITYMYTH
Consider:
Social engineering hacks
Human error as MF experts retire
Mainframe is viewed as a black-box breeds complacency –compounding
the risk
7 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
71% of the world’s mission critical
data is on the mainframe
The mainframe acts as the enterprise IT server
and has more entry and exit vectors.
We must protect the mainframe and all business critical
data as the strategic assets that they are, plus ensure
easily confirmed regulatory compliance.
Years in the making…
Source: Rehabilitating the Perception of Mainframes, Enterprise systems Media, 22 July 2015
8 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
What We Hear From Clients
Regulated data has to be protected,
regardless of what type of server it
sits on or how it got there. That
includes the mainframe, and existing
controls may not cover all of it.
We know where our
sensitive, regulated data is….
It’s in our data center.
Audit
MF Security
analystCISO
The mainframe is now just another always-
on server connected to all the others in our
TCP/IP network. I’m not sure all the data
hosted there is being managed to policy…
We know the mainframe is no longer
isolated from other servers in the network.
We don’t know how much unmanaged
regulated data now resides there…
With the addition of TCP/IP via USS,
mainframe data is fluid – we don’t
know what we don’t know about
what’s being stored there….
MF Security
Director
I need to exploit data’s full value
proposition for my organization
while controlling the risk.
Chief Data
Officer
9 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
http://www.informationisbeautiful.net/visualizations/worlds-biggest-data-breaches-hacks/
10 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
The Impact of Data Theft
Health Insurance
Announced: March 2015
Records stolen: 11M
Cost: To be determined. Facing a class
action lawsuit as well as potential regulatory
violation fines.
Retail
Announced: September 2014
Records stolen: 56M
Cost: $43M and counting. Estimates put this
as high as $10B (includes all remediation
costs borne by the company and consumers)
Health Systems
Announced: August 2014
Records stolen: 4.5M
Cost: $75M – $150M
eCommerce
Announced: May 2014
Records stolen: 233M
Cost: $200M and counting.
Retail
Announced: December 2013
Records stolen: 70M
Cost: $162M and counting. Recent
estimates put this at well over $1B.
Government
Announced: May 2015
Records stolen: 22M
Cost: To be determined. Likely facing a class
action lawsuit as well as others.
Sensitive Data Defined
12 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
PCI DSS Data
Administered
by one body
 Payment
Security Council
Account Data
Cardholder Data Sensitive Authentication Data
Primary Account Number (PAN) Magnetic stripe data
Cardholder Name CAV2/CVC2/CVV2/CID
Expiration Date PINs/PIN blocks
Service Code
13 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
Personally Identifiable Information – PII
PII Attributes
Full Name Date of birth
Home Address Email address
National Identification Number Passport number
Drivers License Number Vehicle registration
Birthplace Genetic information
Telephone number Login name, screen name, nickname, handle
Face, fingerprints, handwriting IP Address
Credit Card Numbers Digital identity
First Name Last Name
Country, state, postcode, city Age
Gender Race
Schools attended Criminal record
Legislated by an large &
growing number of
governmental entities
 Multi-national: EU Data
Protection Directive
 National: Gramm-Leach Bliley
Banking Modernization Act,
Canada Privacy Act
 Local: California SB 1386,
Nevada Statute 603A,
Massachusetts 201 CMR 17.00
14 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
PHI Attributes
Full Name Geographic subdivision
Data elements Telephone number
Fax number Electronic mail address
SSN Medical record number
Health Plan beneficiary number Account number
Certificate/license number Vehicle ID/Serial number/license plate number
Device identifier/serial number Biometric identifier
Full face photograph or image Other unique identifying element
Initially, only US, now
spreading internationally
Legislated by an large &
growing number of
governmental entities
 Multi-national: TBD
 National: US HIPAA /
HITECH ACTs
 Local: TBD
Protected Health Information - PHI
Data Content Discovery on the Mainframe
Existing mainframe content discovery
tools migrate off the mainframe to
PCs or other devices to scan
Why locating data on a mainframe is a problem?
 Report writers extract
production data and data exists
in sequential files or JES spool
 Copies of sensitive production
data exist
 Files with possible sensitive data
are accidentally sent to outside
parties without validation of
content
 Once data is extracted, the
target destination doesn’t match
the security characteristics of
source DB
RESULT
Organizations are neither prepared
for, or confident in an audit!
CHALLENGES REALITY
Why locating data on a mainframe is a problem?
17 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
CA Data Content Discovery
FIND
Set up the scan
Initiate the scan
Provide discovered
results to Security
Administrator
CLASSIFY
Review compliance
results and label
sensitive data
Provide compliance
report to Internal Auditor
PROTECT
Modify access based
on scan results
Confirm successful
audit against
industry regulations
Security Operations Internal Auditor Security Administrator
18 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
Find It: Define Scope
19 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
Classify it
20 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
Account Data
Cardholder Data Sensitive Authentication Data
Primary Account Number (PAN) Magnetic stripe data
Cardholder Name CAV2/CVC2/CVV2/CID
Expiration Date PINs/PIN blocks
Service Code
Classify It: PCI Data
21 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
Classify It: PII Data
PII Attributes
Full Name Date of birth
Home Address Email address
National Identification Number Passport number
Drivers License Number Vehicle registration
Birthplace Genetic information
Telephone number Login name, screen name, nickname, handle
Face, fingerprints, handwriting IP Address
Credit Card Numbers Digital identity
First Name Last Name
Country, state, postcode, city Age
Gender Race
Schools attended Criminal record
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
Custom
Classifier
Quick
Picks
22 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
Classify It: PHI Data
PHI Attributes
Full Name Geographic subdivision
Data elements Telephone number
Fax number Electronic mail address
SSN Medical record number
Health Plan beneficiary number Account number
Certificate/license number Vehicle ID/Serial number/license plate number
Device identifier/serial number Biometric identifier
Full face photograph or image Other unique identifying element
C
Custom
Classifier
Quick
Picks
C
C
C
C
C
C
C
C
C
23 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
Protect It: Who Has Access to the Sensitive Data?
24 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
CA Data Content Discovery Promise
FIND IT CLASSIFY IT PROTECT IT
For CISO, MF Security Director FOR CISO, Internal Audit, Risk Officer
FOR MF Security analysts, MF Data
analyst
The first data-pattern scanning
capability uniquely natively on
mainframe in the market
Simple and Modern GUI along with
Flexible scheduling designed for
both z and non-IBM z personnel
Eliminate risky offloading- with data
security right on the mainframe.
Only Data security product currently
on the market for mainframe to use
specialty engines to reduce upgrade
costs
Gain quick and critical insight about
the potential and magnitude of data
exposure on the mainframe
Prove it to auditors that controls are
checked by data-types to satisfy
regulations
Stay in control – eliminate risk while
reducing costs of data protection
processes
25 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
Product / Technology Architecture
Execution
Policy
Web GUI
Control Scans
Reporting
Classification
Engine:
z/OS
Data Sources
VSAM
DB2
PS
API
3rd party 3rd party
CA Compliance
Event
Manager
PDS/
PDSE
…
Description of Technology
Overview of Technology
 Data Content Discovery
“scans” data, identifying
data vulnerabilities and
risks to compliance
Lands Lightly
 Product has no other CA
product dependencies or
other prerequisites,
installs in <1 day
DCD
Repository
26 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
Data Content Discovery – A critical part of CA’s Security
and Compliance Solution
CA Data
Protection
3rd party DLP
Solution
3rd party DLP
Solution
Big Data
Analytics
Solutions
CA Compliance Event Manager
IBM RACF
CA Top
Secret
CA ACF2
CA Cleanup
In Ideation:
Mainframe
Advanced
Authentication
CA Data
Content
Discovery
CA
Auditor
Secure mainframe assets
Capture events affecting compliance and policy
Discover sensitive data
Extend compliance event data to analytics solutions
Enable secure data in motion across the enterprise
Security
Administrator
Big Data AnalystAuditor
Planned
Available
Non-CA
Product
27 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
Results
There is stray, unmanaged, unprotected data on your
mainframe – regulated, sensitive data that will damage the
enterprise if compromised
Find it, classify it, protect it with DCD
Summary
A Few Words to Review
28 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
Recommended Sessions
SESSION # TITLE DATE/TIME
Tech Talk
Isn’t one authentication mechanism on z Systems™
enough?
11/18 – 4:30pm
Mainframe Content Center
Mainframe
Theater
Panel Discussion: Is Complacency Around Mainframe
Security a Disaster Waiting to Happen?
11/18 – 3:45pm
Mainframe Theater
Tech Talk
The Known Unknown – Finding lost, abandoned, and
hidden regulated data on the Mainframe
11/19 – 12:15pm
Mainframe Content Center
MFX26S
How to Increase User Accountability by Eliminating the
Default User in Unix System Services
11/19 – 1:00pm
Breakers I
MFX47S
Top 10 things you shout NOT forget when evaluating
your security implementation
11/19 – 2:00pm
Breakers I
29 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
Follow Conversations in the Mainframe Content Center
 CA Data Content
Discovery
 CA ACF2 ™ for z/OS
 CA Top Secret® for z/OS
 CA Cleanup
 CA Auditor
 Advanced Authentication
Nov 18th @ 4:30pm
 The Known Unknown -
Nov 19th @ 12:15pm
30 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
Q & A
31 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD
For More Information
To learn more, please visit:
http://cainc.to/Nv2VOe
CA World ’15

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Locating Unmanaged but Regulated Data on System z: CA Data Content Discovery

  • 1. Locating Unmanaged but Regulated Data on z Systems: CA Data Content Discovery Mary Ann Furno Mainframe CA Technologies Director, Software Engineering MFX25S
  • 2. 2 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD For Informational Purposes Only Terms of this Presentation © 2015 CA. All rights reserved. All trademarks referenced herein belong to their respective companies. The presentation provided at CA World 2015 is intended for information purposes only and does not form any type of warranty. Some of the specific slides with customer references relate to customer's specific use and experience of CA products and solutions so actual results may vary. Certain information in this presentation may outline CA’s general product direction. This presentation shall not serve to (i) affect the rights and/or obligations of CA or its licensees under any existing or future license agreement or services agreement relating to any CA software product; or (ii) amend any product documentation or specifications for any CA software product. This presentation is based on current information and resource allocations as of November 18, 2015, and is subject to change or withdrawal by CA at any time without notice. The development, release and timing of any features or functionality described in this presentation remain at CA’s sole discretion. Notwithstanding anything in this presentation to the contrary, upon the general availability of any future CA product release referenced in this presentation, CA may make such release available to new licensees in the form of a regularly scheduled major product release. Such release may be made available to licensees of the product who are active subscribers to CA maintenance and support, on a when and if- available basis. The information in this presentation is not deemed to be incorporated into any contract.
  • 3. 3 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD Abstract CA Data Content Discovery helps you identify data exposure risks on z Systems by scanning through the mainframe data infrastructure. By discovering where the data is located, classifying the data to determine sensitivity level, and providing comprehensive reporting on the scan results, data can be adequately protected and exposure risks can be mitigated. Mary Ann Furno CA Technologies Director, Software Engineering
  • 4. 4 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD Agenda CISOS, REGULATED DATA, AND THE MAINFRAME SENSITIVE DATA DEFINED DATA CONTENT DISCOVERY ON THE MAINFRAME DATA CONTENT DISCOVERY ROADMAP 1 2 3 4
  • 6. 6 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD The Mainframe has never been hacked! Mainframe data stays on the mainframe; so it is safe! Data is fluid in today’s world. Data analytics; cloud Marriage of MF data and non MF data Mainframe is well understood and covered under three lines of risk control– Operational, Compliance and Internal audit The Current State REALITYMYTH Consider: Social engineering hacks Human error as MF experts retire Mainframe is viewed as a black-box breeds complacency –compounding the risk
  • 7. 7 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD 71% of the world’s mission critical data is on the mainframe The mainframe acts as the enterprise IT server and has more entry and exit vectors. We must protect the mainframe and all business critical data as the strategic assets that they are, plus ensure easily confirmed regulatory compliance. Years in the making… Source: Rehabilitating the Perception of Mainframes, Enterprise systems Media, 22 July 2015
  • 8. 8 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD What We Hear From Clients Regulated data has to be protected, regardless of what type of server it sits on or how it got there. That includes the mainframe, and existing controls may not cover all of it. We know where our sensitive, regulated data is…. It’s in our data center. Audit MF Security analystCISO The mainframe is now just another always- on server connected to all the others in our TCP/IP network. I’m not sure all the data hosted there is being managed to policy… We know the mainframe is no longer isolated from other servers in the network. We don’t know how much unmanaged regulated data now resides there… With the addition of TCP/IP via USS, mainframe data is fluid – we don’t know what we don’t know about what’s being stored there…. MF Security Director I need to exploit data’s full value proposition for my organization while controlling the risk. Chief Data Officer
  • 9. 9 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD http://www.informationisbeautiful.net/visualizations/worlds-biggest-data-breaches-hacks/
  • 10. 10 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD The Impact of Data Theft Health Insurance Announced: March 2015 Records stolen: 11M Cost: To be determined. Facing a class action lawsuit as well as potential regulatory violation fines. Retail Announced: September 2014 Records stolen: 56M Cost: $43M and counting. Estimates put this as high as $10B (includes all remediation costs borne by the company and consumers) Health Systems Announced: August 2014 Records stolen: 4.5M Cost: $75M – $150M eCommerce Announced: May 2014 Records stolen: 233M Cost: $200M and counting. Retail Announced: December 2013 Records stolen: 70M Cost: $162M and counting. Recent estimates put this at well over $1B. Government Announced: May 2015 Records stolen: 22M Cost: To be determined. Likely facing a class action lawsuit as well as others.
  • 12. 12 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD PCI DSS Data Administered by one body  Payment Security Council Account Data Cardholder Data Sensitive Authentication Data Primary Account Number (PAN) Magnetic stripe data Cardholder Name CAV2/CVC2/CVV2/CID Expiration Date PINs/PIN blocks Service Code
  • 13. 13 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD Personally Identifiable Information – PII PII Attributes Full Name Date of birth Home Address Email address National Identification Number Passport number Drivers License Number Vehicle registration Birthplace Genetic information Telephone number Login name, screen name, nickname, handle Face, fingerprints, handwriting IP Address Credit Card Numbers Digital identity First Name Last Name Country, state, postcode, city Age Gender Race Schools attended Criminal record Legislated by an large & growing number of governmental entities  Multi-national: EU Data Protection Directive  National: Gramm-Leach Bliley Banking Modernization Act, Canada Privacy Act  Local: California SB 1386, Nevada Statute 603A, Massachusetts 201 CMR 17.00
  • 14. 14 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD PHI Attributes Full Name Geographic subdivision Data elements Telephone number Fax number Electronic mail address SSN Medical record number Health Plan beneficiary number Account number Certificate/license number Vehicle ID/Serial number/license plate number Device identifier/serial number Biometric identifier Full face photograph or image Other unique identifying element Initially, only US, now spreading internationally Legislated by an large & growing number of governmental entities  Multi-national: TBD  National: US HIPAA / HITECH ACTs  Local: TBD Protected Health Information - PHI
  • 15. Data Content Discovery on the Mainframe
  • 16. Existing mainframe content discovery tools migrate off the mainframe to PCs or other devices to scan Why locating data on a mainframe is a problem?  Report writers extract production data and data exists in sequential files or JES spool  Copies of sensitive production data exist  Files with possible sensitive data are accidentally sent to outside parties without validation of content  Once data is extracted, the target destination doesn’t match the security characteristics of source DB RESULT Organizations are neither prepared for, or confident in an audit! CHALLENGES REALITY Why locating data on a mainframe is a problem?
  • 17. 17 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD CA Data Content Discovery FIND Set up the scan Initiate the scan Provide discovered results to Security Administrator CLASSIFY Review compliance results and label sensitive data Provide compliance report to Internal Auditor PROTECT Modify access based on scan results Confirm successful audit against industry regulations Security Operations Internal Auditor Security Administrator
  • 18. 18 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD Find It: Define Scope
  • 19. 19 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD Classify it
  • 20. 20 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD Account Data Cardholder Data Sensitive Authentication Data Primary Account Number (PAN) Magnetic stripe data Cardholder Name CAV2/CVC2/CVV2/CID Expiration Date PINs/PIN blocks Service Code Classify It: PCI Data
  • 21. 21 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD Classify It: PII Data PII Attributes Full Name Date of birth Home Address Email address National Identification Number Passport number Drivers License Number Vehicle registration Birthplace Genetic information Telephone number Login name, screen name, nickname, handle Face, fingerprints, handwriting IP Address Credit Card Numbers Digital identity First Name Last Name Country, state, postcode, city Age Gender Race Schools attended Criminal record C C C C C C C C C C C C C C C Custom Classifier Quick Picks
  • 22. 22 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD Classify It: PHI Data PHI Attributes Full Name Geographic subdivision Data elements Telephone number Fax number Electronic mail address SSN Medical record number Health Plan beneficiary number Account number Certificate/license number Vehicle ID/Serial number/license plate number Device identifier/serial number Biometric identifier Full face photograph or image Other unique identifying element C Custom Classifier Quick Picks C C C C C C C C C
  • 23. 23 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD Protect It: Who Has Access to the Sensitive Data?
  • 24. 24 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD CA Data Content Discovery Promise FIND IT CLASSIFY IT PROTECT IT For CISO, MF Security Director FOR CISO, Internal Audit, Risk Officer FOR MF Security analysts, MF Data analyst The first data-pattern scanning capability uniquely natively on mainframe in the market Simple and Modern GUI along with Flexible scheduling designed for both z and non-IBM z personnel Eliminate risky offloading- with data security right on the mainframe. Only Data security product currently on the market for mainframe to use specialty engines to reduce upgrade costs Gain quick and critical insight about the potential and magnitude of data exposure on the mainframe Prove it to auditors that controls are checked by data-types to satisfy regulations Stay in control – eliminate risk while reducing costs of data protection processes
  • 25. 25 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD Product / Technology Architecture Execution Policy Web GUI Control Scans Reporting Classification Engine: z/OS Data Sources VSAM DB2 PS API 3rd party 3rd party CA Compliance Event Manager PDS/ PDSE … Description of Technology Overview of Technology  Data Content Discovery “scans” data, identifying data vulnerabilities and risks to compliance Lands Lightly  Product has no other CA product dependencies or other prerequisites, installs in <1 day DCD Repository
  • 26. 26 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD Data Content Discovery – A critical part of CA’s Security and Compliance Solution CA Data Protection 3rd party DLP Solution 3rd party DLP Solution Big Data Analytics Solutions CA Compliance Event Manager IBM RACF CA Top Secret CA ACF2 CA Cleanup In Ideation: Mainframe Advanced Authentication CA Data Content Discovery CA Auditor Secure mainframe assets Capture events affecting compliance and policy Discover sensitive data Extend compliance event data to analytics solutions Enable secure data in motion across the enterprise Security Administrator Big Data AnalystAuditor Planned Available Non-CA Product
  • 27. 27 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD Results There is stray, unmanaged, unprotected data on your mainframe – regulated, sensitive data that will damage the enterprise if compromised Find it, classify it, protect it with DCD Summary A Few Words to Review
  • 28. 28 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD Recommended Sessions SESSION # TITLE DATE/TIME Tech Talk Isn’t one authentication mechanism on z Systems™ enough? 11/18 – 4:30pm Mainframe Content Center Mainframe Theater Panel Discussion: Is Complacency Around Mainframe Security a Disaster Waiting to Happen? 11/18 – 3:45pm Mainframe Theater Tech Talk The Known Unknown – Finding lost, abandoned, and hidden regulated data on the Mainframe 11/19 – 12:15pm Mainframe Content Center MFX26S How to Increase User Accountability by Eliminating the Default User in Unix System Services 11/19 – 1:00pm Breakers I MFX47S Top 10 things you shout NOT forget when evaluating your security implementation 11/19 – 2:00pm Breakers I
  • 29. 29 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD Follow Conversations in the Mainframe Content Center  CA Data Content Discovery  CA ACF2 ™ for z/OS  CA Top Secret® for z/OS  CA Cleanup  CA Auditor  Advanced Authentication Nov 18th @ 4:30pm  The Known Unknown - Nov 19th @ 12:15pm
  • 30. 30 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD Q & A
  • 31. 31 © 2015 CA. ALL RIGHTS RESERVED.@CAWORLD #CAWORLD For More Information To learn more, please visit: http://cainc.to/Nv2VOe CA World ’15