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Building Secure Hadoop
Environments

© 2012 Datameer, Inc. All rights reserved.
© 2012 Datameer, Inc. All rights reserved.
View the full recording
You can view the full recording of this ondemand webinar with slides at:
http://info.datameer.com/Slideshare-BuildingSecure-Hadoop-Environments.html

© 2012 Datameer, Inc. All rights reserved.
About our Speaker
Karen Hsu
With over 15 years of experience in
enterprise software, Karen Hsu has coauthored 4 patents and worked in a variety
of engineering, marketing and sales roles.
Most recently she came from Informatica
where she worked with the start-ups
Informatica purchased to bring data
quality, master data management, B2B and
data security solutions to market.
Karen has a Bachelors of Science degree
in Management Science and Engineering
from Stanford University.

© 2012 Datameer, Inc. All rights reserved.
About our Speaker
Filip Slunecko
Filip is part of the Customer support team at
Datameer.
He is a Linux professional and Python
enthusiast. Before joining Datameer, he was on
the Hadoop team at AVG, an antivirus/security
company.
Filip now uses his 8 years experience with Linux
servers and Hadoop security to help Datameer
customers.

© 2012 Datameer, Inc. All rights reserved.
Building Secure Hadoop
Environments

© 2012 Datameer, Inc. All rights reserved.
© 2012 Datameer, Inc. All rights reserved.
Agenda
Challenges and use cases
Hadoop security landscape
Components for building successful
Hadoop environments
Call to Action

© 2012 Datameer, Inc. All rights reserved.
Hadoop Data Security Challenges
Architectural issues
Hadoop security is developing
Vendors offer bolt-on solutions
To add security capabilities into a big data environment, the
capabilities need to scale with the data… Most security tools fail
to scale and perform with big data environments.
- Adrian Lane, Securosis
Securosis, Oct 12, 2012
© 2012 Datameer, Inc. All rights reserved.
Hadoop Security Use Cases
Use Case

Requirement

Example

Description

Role based
access

Data access is
restricted
through the
abstraction
layer

Users have a view of
data in Hadoop they
can manipulate

Transformation
of sensitive
values during
load

Data is
transformed,
masked, or
encrypted.

Cluster is copied and
then
masked/transformed
so that analysts work
on anonymized data

© 2012 Datameer, Inc. All rights reserved.
Role Based Access

Data Access

Pig / Hive

Map-Reduce

Restrict View
HDFS

© 2012 Datameer, Inc. All rights reserved.
Transformation of Sensitive Values

Data Access

Load

Map-Reduce

Transform Data
HDFS

© 2012 Datameer, Inc. All rights reserved.
Hybrid of Role Based Access and
Transformation of Sensitive Values
Data Access
Load

Map-Reduce

Transform

Restrict View

HDFS

© 2012 Datameer, Inc. All rights reserved.
Hadoop Security Offerings
Type

Description

Example vendors

Role based access control

Use LDAP / Active Directory (AD)
authentication to identify and
manage users. Leveraging
Kerberos to provide mutual
authentication

Encryption

•
•
•

Masking

Data Masking performed before
load

Block level encryption

Linux directory level encryption
with external key store

File encryption
Disk encryption
Format preserving encryption

© 2012 Datameer, Inc. All rights reserved.
Components for Building Secure
Hadoop Environment
Secure access – SSL
Access controls
Secure authentication
Kerberos
Logging – auditing
File Encryption
Disk encryption

© 2012 Datameer, Inc. All rights reserved.
Secure access

© 2012 Datameer, Inc. All rights reserved.
Access Controls
Datameer Example
Object permission
Roles
LDAP
Kerberos
Impersonation

© 2012 Datameer, Inc. All rights reserved.
Object Permission
Datameer Example
Object types
Import jobs
Data links
Workbooks
Export job

Info graphics

© 2012 Datameer, Inc. All rights reserved.
Roles
Datameer Example

© 2012 Datameer, Inc. All rights reserved.
Remote Authenticator
Datameer Example

Integrating into an existing infrastructure
Active directory support
Import groups and users to Datameer
Centralized user management

© 2012 Datameer, Inc. All rights reserved.
Kerberos

© 2012 Datameer, Inc. All rights reserved.
Impersonation

© 2012 Datameer, Inc. All rights reserved.
Demonstration

© 2012 Datameer, Inc. All rights reserved.
Disk Encryption
Why it’s important
• 1 year - 2%
• 2 year - 6-8%
Criteria for success
• Encryption per process
• Key management
• Safe and in full compliance with HIPAA, PCIDSS, FERPA

© 2012 Datameer, Inc. All rights reserved.
File Encryption
Emerging Technology

Intel Hadoop
Project Rhino
• Encryption and key management.
• A common authorization framework.
• Token based authentication and single sign on.
• Improve audit logging.

© 2012 Datameer, Inc. All rights reserved.
Logging and Auditing

Datameer
UI Access

Job
execution

Hadoop
File
access

Job runs

© 2012 Datameer, Inc. All rights reserved.
Logging and Auditing

Centralized logging
Collectors

Storage

Real Time Search

Visualization

Datameer

Datameer*

Katta

Datameer

Splunk

Splunk

Elasticsearch

Splunk

Flume

Elasticsearch

Solr

Greylog

Greylog

Solr

Graphite

Hive

© 2012 Datameer, Inc. All rights reserved.
Recap
Challenges and use cases
Hadoop security landscape
Components for building successful Hadoop
environments
• Secure access – SSL
• Access controls
• Secure authentication
• Kerberos
• Logging – auditing
• File Encryption
• Disk encryption
© 2012 Datameer, Inc. All rights reserved.
Call to Action
Contact
• Filip Slunecko
fslunecko@datameer.com
• Karen Hsu
khsu@datameer.com

Implementing Hadoop Security
Workshop
• Contact
marketing@datameer.com for
more details

Meet us at
Discover Big Data 8 City Workshop
near you!
http://info.datameer.com/Discove
r-Big-Data-RoadShow.html

www.datameer.com

© 2012 Datameer, Inc. All rights reserved.
Online Resources




Try Datameer: www.datameer.com
Follow us on Twitter @datameer

© 2012 Datameer, Inc. All rights reserved.

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Is Your Hadoop Environment Secure?

  • 1. Building Secure Hadoop Environments © 2012 Datameer, Inc. All rights reserved. © 2012 Datameer, Inc. All rights reserved.
  • 2. View the full recording You can view the full recording of this ondemand webinar with slides at: http://info.datameer.com/Slideshare-BuildingSecure-Hadoop-Environments.html © 2012 Datameer, Inc. All rights reserved.
  • 3. About our Speaker Karen Hsu With over 15 years of experience in enterprise software, Karen Hsu has coauthored 4 patents and worked in a variety of engineering, marketing and sales roles. Most recently she came from Informatica where she worked with the start-ups Informatica purchased to bring data quality, master data management, B2B and data security solutions to market. Karen has a Bachelors of Science degree in Management Science and Engineering from Stanford University. © 2012 Datameer, Inc. All rights reserved.
  • 4. About our Speaker Filip Slunecko Filip is part of the Customer support team at Datameer. He is a Linux professional and Python enthusiast. Before joining Datameer, he was on the Hadoop team at AVG, an antivirus/security company. Filip now uses his 8 years experience with Linux servers and Hadoop security to help Datameer customers. © 2012 Datameer, Inc. All rights reserved.
  • 5. Building Secure Hadoop Environments © 2012 Datameer, Inc. All rights reserved. © 2012 Datameer, Inc. All rights reserved.
  • 6. Agenda Challenges and use cases Hadoop security landscape Components for building successful Hadoop environments Call to Action © 2012 Datameer, Inc. All rights reserved.
  • 7. Hadoop Data Security Challenges Architectural issues Hadoop security is developing Vendors offer bolt-on solutions To add security capabilities into a big data environment, the capabilities need to scale with the data… Most security tools fail to scale and perform with big data environments. - Adrian Lane, Securosis Securosis, Oct 12, 2012 © 2012 Datameer, Inc. All rights reserved.
  • 8. Hadoop Security Use Cases Use Case Requirement Example Description Role based access Data access is restricted through the abstraction layer Users have a view of data in Hadoop they can manipulate Transformation of sensitive values during load Data is transformed, masked, or encrypted. Cluster is copied and then masked/transformed so that analysts work on anonymized data © 2012 Datameer, Inc. All rights reserved.
  • 9. Role Based Access Data Access Pig / Hive Map-Reduce Restrict View HDFS © 2012 Datameer, Inc. All rights reserved.
  • 10. Transformation of Sensitive Values Data Access Load Map-Reduce Transform Data HDFS © 2012 Datameer, Inc. All rights reserved.
  • 11. Hybrid of Role Based Access and Transformation of Sensitive Values Data Access Load Map-Reduce Transform Restrict View HDFS © 2012 Datameer, Inc. All rights reserved.
  • 12. Hadoop Security Offerings Type Description Example vendors Role based access control Use LDAP / Active Directory (AD) authentication to identify and manage users. Leveraging Kerberos to provide mutual authentication Encryption • • • Masking Data Masking performed before load Block level encryption Linux directory level encryption with external key store File encryption Disk encryption Format preserving encryption © 2012 Datameer, Inc. All rights reserved.
  • 13. Components for Building Secure Hadoop Environment Secure access – SSL Access controls Secure authentication Kerberos Logging – auditing File Encryption Disk encryption © 2012 Datameer, Inc. All rights reserved.
  • 14. Secure access © 2012 Datameer, Inc. All rights reserved.
  • 15. Access Controls Datameer Example Object permission Roles LDAP Kerberos Impersonation © 2012 Datameer, Inc. All rights reserved.
  • 16. Object Permission Datameer Example Object types Import jobs Data links Workbooks Export job Info graphics © 2012 Datameer, Inc. All rights reserved.
  • 17. Roles Datameer Example © 2012 Datameer, Inc. All rights reserved.
  • 18. Remote Authenticator Datameer Example Integrating into an existing infrastructure Active directory support Import groups and users to Datameer Centralized user management © 2012 Datameer, Inc. All rights reserved.
  • 19. Kerberos © 2012 Datameer, Inc. All rights reserved.
  • 20. Impersonation © 2012 Datameer, Inc. All rights reserved.
  • 21. Demonstration © 2012 Datameer, Inc. All rights reserved.
  • 22. Disk Encryption Why it’s important • 1 year - 2% • 2 year - 6-8% Criteria for success • Encryption per process • Key management • Safe and in full compliance with HIPAA, PCIDSS, FERPA © 2012 Datameer, Inc. All rights reserved.
  • 23. File Encryption Emerging Technology Intel Hadoop Project Rhino • Encryption and key management. • A common authorization framework. • Token based authentication and single sign on. • Improve audit logging. © 2012 Datameer, Inc. All rights reserved.
  • 24. Logging and Auditing Datameer UI Access Job execution Hadoop File access Job runs © 2012 Datameer, Inc. All rights reserved.
  • 25. Logging and Auditing Centralized logging Collectors Storage Real Time Search Visualization Datameer Datameer* Katta Datameer Splunk Splunk Elasticsearch Splunk Flume Elasticsearch Solr Greylog Greylog Solr Graphite Hive © 2012 Datameer, Inc. All rights reserved.
  • 26. Recap Challenges and use cases Hadoop security landscape Components for building successful Hadoop environments • Secure access – SSL • Access controls • Secure authentication • Kerberos • Logging – auditing • File Encryption • Disk encryption © 2012 Datameer, Inc. All rights reserved.
  • 27. Call to Action Contact • Filip Slunecko fslunecko@datameer.com • Karen Hsu khsu@datameer.com Implementing Hadoop Security Workshop • Contact marketing@datameer.com for more details Meet us at Discover Big Data 8 City Workshop near you! http://info.datameer.com/Discove r-Big-Data-RoadShow.html www.datameer.com © 2012 Datameer, Inc. All rights reserved.
  • 28. Online Resources   Try Datameer: www.datameer.com Follow us on Twitter @datameer © 2012 Datameer, Inc. All rights reserved.

Editor's Notes

  1. Architectural issuesBig data environments do not typically offer no finer granularity of access than schema levelLack of secure inter-node communication (create separate layer so customers don’t have to worry about this)Hadoop security is developingImprovements to role-based HDFS security are in progressOpensource projects are just beginningVendors offer immature solutionsTrying to apply traditional methods to HadoopCreate a central chokepoint and are not operating at the node levelLack of solutions in production
  2. The big data users I have spoken with about data security agreed that data masking at that scale is infeasible. Given the rate of data insertion (also called ‘velocity’), masking sensitive data before loading it into a cluster would require “an entire ETL cluster to front the Hadoop cluster”. But apparently it’s doable, and Netflix did just that – fronted its analytics cluster with a data transformation cluster, all within EC2. 500 nodes massaging data for another 500 nodes. While the ETL cluster is not used for masking, note that it is about the same size as the analysis cluster. It’s this one-to-one mapping that I often worry about with security. Ask yourself, “Do we need another whole cluster for masking?” No? Then what about NoSQL activity monitoring? What about IAM, application monitoring, and any other security tasks. Do you start to see the problem with bolting on security? Logging and auditing are embeddable – most everything else is not.
  3. Kerberos to provide mutual authentication—both the user and the server verify each other’s identityGazzang – block level for big data
  4. A proper infrastructure PKI inside an organizationCert The warning screen – users are used to certificate warnings CDH4.1 – Kerberos SSLDisable Hadoop we access
  5. Object typesUnix based permResults sharingEasy to understand and audit
  6. Granular rolesPer type of an object not just per an objectExample:Hadoop admin – role – can access Hadoop settings and create import jobs – do not have access to data
  7. Different group in an organization – more security – Hadoop admins do not have rights to change add/remove p. from groups
  8. Join to a company AD infrastructure.Adopted by Hadoop as an authentication mechanismIntegration with other services across platforms – zookeeper, For example MSSQL services
  9. Delegation – Datameer can run jobs as a owner of the jobWith imp only owner can access his own file.When user is deleted from system ……Jobs are run as an owner of the job and stored
  10. - Show access rights, role screen, LDAP screen, Kerberos setup
  11. Intel – Implemented in Hadoop APIYoung project – others – future will shows if others participate – Cloudera ….Others: Volateg. Preterit – not open source and not wildly used
  12. Detailed information about user access Detailed information job runs – dependent on Hadoop logs
  13. Datameer for big data.Use Datameer to analyze Datameer access logs.Abnormality detectionSecurity breach detection.Behavior analysis.* HDFS - Hadoop