Submit Search
Upload
Big Data Security and Governance
•
5 likes
•
3,808 views
DataWorks Summit/Hadoop Summit
Follow
Big Data Security and Governance
Read less
Read more
Technology
Report
Share
Report
Share
1 of 36
Download now
Download to read offline
Recommended
Enterprise Cybersecurity: From Strategy to Operating Model
Enterprise Cybersecurity: From Strategy to Operating Model
Eryk Budi Pratama
Data Lake Architecture – Modern Strategies & Approaches
Data Lake Architecture – Modern Strategies & Approaches
DATAVERSITY
Data classification-policy
Data classification-policy
Coi Xay
The Path to Data and Analytics Modernization
The Path to Data and Analytics Modernization
Analytics8
Snowflake Data Science and AI/ML at Scale
Snowflake Data Science and AI/ML at Scale
Adam Doyle
BI Consultancy - Data, Analytics and Strategy
BI Consultancy - Data, Analytics and Strategy
Shivam Dhawan
Linking Data Governance to Business Goals
Linking Data Governance to Business Goals
Precisely
Security architecture
Security architecture
Duncan Unwin
Recommended
Enterprise Cybersecurity: From Strategy to Operating Model
Enterprise Cybersecurity: From Strategy to Operating Model
Eryk Budi Pratama
Data Lake Architecture – Modern Strategies & Approaches
Data Lake Architecture – Modern Strategies & Approaches
DATAVERSITY
Data classification-policy
Data classification-policy
Coi Xay
The Path to Data and Analytics Modernization
The Path to Data and Analytics Modernization
Analytics8
Snowflake Data Science and AI/ML at Scale
Snowflake Data Science and AI/ML at Scale
Adam Doyle
BI Consultancy - Data, Analytics and Strategy
BI Consultancy - Data, Analytics and Strategy
Shivam Dhawan
Linking Data Governance to Business Goals
Linking Data Governance to Business Goals
Precisely
Security architecture
Security architecture
Duncan Unwin
Big data architectures and the data lake
Big data architectures and the data lake
James Serra
TOP_407070357-Data-Governance-Playbook.pptx
TOP_407070357-Data-Governance-Playbook.pptx
SabrinaLameiras1
Classifying Data to Help Secure Business Information - Template fromMicrosoft
Classifying Data to Help Secure Business Information - Template fromMicrosoft
David J Rosenthal
Creating a Data-Driven Organization, Crunchconf, October 2015
Creating a Data-Driven Organization, Crunchconf, October 2015
Carl Anderson
How to Build Data Governance Programs That Last: A Business-First Approach
How to Build Data Governance Programs That Last: A Business-First Approach
Precisely
Putting the Ops in DataOps: Orchestrate the Flow of Data Across Data Pipelines
Putting the Ops in DataOps: Orchestrate the Flow of Data Across Data Pipelines
DATAVERSITY
Data Warehousing Trends, Best Practices, and Future Outlook
Data Warehousing Trends, Best Practices, and Future Outlook
James Serra
Information security
Information security
avinashbalakrishnan2
Collibra - Forrester Presentation : Data Governance 2.0
Collibra - Forrester Presentation : Data Governance 2.0
Guillaume LE GALIARD
data-analytics-strategy-ebook.pptx
data-analytics-strategy-ebook.pptx
MohamedHendawy17
Building a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business Goals
DATAVERSITY
The Data Driven University - Automating Data Governance and Stewardship in Au...
The Data Driven University - Automating Data Governance and Stewardship in Au...
Pieter De Leenheer
Data Governance in a big data era
Data Governance in a big data era
Pieter De Leenheer
Enterprise Data Architecture Deliverables
Enterprise Data Architecture Deliverables
Lars E Martinsson
Rethinking Trust in Data
Rethinking Trust in Data
DATAVERSITY
Data-Ed Slides: Best Practices in Data Stewardship (Technical)
Data-Ed Slides: Best Practices in Data Stewardship (Technical)
DATAVERSITY
Designing An Enterprise Data Fabric
Designing An Enterprise Data Fabric
Alan McSweeney
Data platform architecture
Data platform architecture
Sudheer Kondla
Who Should Own Data Governance – IT or Business?
Who Should Own Data Governance – IT or Business?
DATAVERSITY
Data Quality Strategy: A Step-by-Step Approach
Data Quality Strategy: A Step-by-Step Approach
FindWhitePapers
Balancing Mobile UX & Security: An API Management Perspective Presentation fr...
Balancing Mobile UX & Security: An API Management Perspective Presentation fr...
CA API Management
Open-BDA Hadoop Summt 2014 - Post Summit Report
Open-BDA Hadoop Summt 2014 - Post Summit Report
Innovative Management Services
More Related Content
What's hot
Big data architectures and the data lake
Big data architectures and the data lake
James Serra
TOP_407070357-Data-Governance-Playbook.pptx
TOP_407070357-Data-Governance-Playbook.pptx
SabrinaLameiras1
Classifying Data to Help Secure Business Information - Template fromMicrosoft
Classifying Data to Help Secure Business Information - Template fromMicrosoft
David J Rosenthal
Creating a Data-Driven Organization, Crunchconf, October 2015
Creating a Data-Driven Organization, Crunchconf, October 2015
Carl Anderson
How to Build Data Governance Programs That Last: A Business-First Approach
How to Build Data Governance Programs That Last: A Business-First Approach
Precisely
Putting the Ops in DataOps: Orchestrate the Flow of Data Across Data Pipelines
Putting the Ops in DataOps: Orchestrate the Flow of Data Across Data Pipelines
DATAVERSITY
Data Warehousing Trends, Best Practices, and Future Outlook
Data Warehousing Trends, Best Practices, and Future Outlook
James Serra
Information security
Information security
avinashbalakrishnan2
Collibra - Forrester Presentation : Data Governance 2.0
Collibra - Forrester Presentation : Data Governance 2.0
Guillaume LE GALIARD
data-analytics-strategy-ebook.pptx
data-analytics-strategy-ebook.pptx
MohamedHendawy17
Building a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business Goals
DATAVERSITY
The Data Driven University - Automating Data Governance and Stewardship in Au...
The Data Driven University - Automating Data Governance and Stewardship in Au...
Pieter De Leenheer
Data Governance in a big data era
Data Governance in a big data era
Pieter De Leenheer
Enterprise Data Architecture Deliverables
Enterprise Data Architecture Deliverables
Lars E Martinsson
Rethinking Trust in Data
Rethinking Trust in Data
DATAVERSITY
Data-Ed Slides: Best Practices in Data Stewardship (Technical)
Data-Ed Slides: Best Practices in Data Stewardship (Technical)
DATAVERSITY
Designing An Enterprise Data Fabric
Designing An Enterprise Data Fabric
Alan McSweeney
Data platform architecture
Data platform architecture
Sudheer Kondla
Who Should Own Data Governance – IT or Business?
Who Should Own Data Governance – IT or Business?
DATAVERSITY
Data Quality Strategy: A Step-by-Step Approach
Data Quality Strategy: A Step-by-Step Approach
FindWhitePapers
What's hot
(20)
Big data architectures and the data lake
Big data architectures and the data lake
TOP_407070357-Data-Governance-Playbook.pptx
TOP_407070357-Data-Governance-Playbook.pptx
Classifying Data to Help Secure Business Information - Template fromMicrosoft
Classifying Data to Help Secure Business Information - Template fromMicrosoft
Creating a Data-Driven Organization, Crunchconf, October 2015
Creating a Data-Driven Organization, Crunchconf, October 2015
How to Build Data Governance Programs That Last: A Business-First Approach
How to Build Data Governance Programs That Last: A Business-First Approach
Putting the Ops in DataOps: Orchestrate the Flow of Data Across Data Pipelines
Putting the Ops in DataOps: Orchestrate the Flow of Data Across Data Pipelines
Data Warehousing Trends, Best Practices, and Future Outlook
Data Warehousing Trends, Best Practices, and Future Outlook
Information security
Information security
Collibra - Forrester Presentation : Data Governance 2.0
Collibra - Forrester Presentation : Data Governance 2.0
data-analytics-strategy-ebook.pptx
data-analytics-strategy-ebook.pptx
Building a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business Goals
The Data Driven University - Automating Data Governance and Stewardship in Au...
The Data Driven University - Automating Data Governance and Stewardship in Au...
Data Governance in a big data era
Data Governance in a big data era
Enterprise Data Architecture Deliverables
Enterprise Data Architecture Deliverables
Rethinking Trust in Data
Rethinking Trust in Data
Data-Ed Slides: Best Practices in Data Stewardship (Technical)
Data-Ed Slides: Best Practices in Data Stewardship (Technical)
Designing An Enterprise Data Fabric
Designing An Enterprise Data Fabric
Data platform architecture
Data platform architecture
Who Should Own Data Governance – IT or Business?
Who Should Own Data Governance – IT or Business?
Data Quality Strategy: A Step-by-Step Approach
Data Quality Strategy: A Step-by-Step Approach
Viewers also liked
Balancing Mobile UX & Security: An API Management Perspective Presentation fr...
Balancing Mobile UX & Security: An API Management Perspective Presentation fr...
CA API Management
Open-BDA Hadoop Summt 2014 - Post Summit Report
Open-BDA Hadoop Summt 2014 - Post Summit Report
Innovative Management Services
MATATABI: Cyber Threat Analysis and Defense Platform using Huge Amount of Dat...
MATATABI: Cyber Threat Analysis and Defense Platform using Huge Amount of Dat...
APNIC
Open-BDA - Big Data Hadoop Developer Training 10th & 11th June
Open-BDA - Big Data Hadoop Developer Training 10th & 11th June
Innovative Management Services
BigDataEurope - Big Data & Energy
BigDataEurope - Big Data & Energy
BigData_Europe
Big Data Security Intelligence and Analytics for Advanced Threat Protection
Big Data Security Intelligence and Analytics for Advanced Threat Protection
Blue Coat
Enterprise Approach towards Cost Savings and Enterprise Agility
Enterprise Approach towards Cost Savings and Enterprise Agility
NUS-ISS
Add
Add
I3E Technologies
To Serve and Protect: Making Sense of Hadoop Security
To Serve and Protect: Making Sense of Hadoop Security
Inside Analysis
"Big Data" in the Energy Industry
"Big Data" in the Energy Industry
Paige Bailey
Generating Insight from Big Data in Energy and the Environment
Generating Insight from Big Data in Energy and the Environment
David Wallom
Building hadoop based big data environment
Building hadoop based big data environment
Evans Ye
Hdp security overview
Hdp security overview
Hortonworks
REAL-TIME BIG DATA ANALYTICAL ARCHITECTURE FOR REMOTE SENSING APPLICATION
REAL-TIME BIG DATA ANALYTICAL ARCHITECTURE FOR REMOTE SENSING APPLICATION
I3E Technologies
Smart Analytics For The Utility Sector
Smart Analytics For The Utility Sector
Herman Bosker
Building Hadoop Data Applications with Kite by Tom White
Building Hadoop Data Applications with Kite by Tom White
The Hive
Demystify big data data science
Demystify big data data science
Mahesh Kumar CV
Hadoop security
Hadoop security
Shivaji Dutta
Big Data, Big Content, and Aligning Your Storage Strategy
Big Data, Big Content, and Aligning Your Storage Strategy
Hitachi Vantara
Mr. satish kumar, schnieder electric
Mr. satish kumar, schnieder electric
Rohan Pinto
Viewers also liked
(20)
Balancing Mobile UX & Security: An API Management Perspective Presentation fr...
Balancing Mobile UX & Security: An API Management Perspective Presentation fr...
Open-BDA Hadoop Summt 2014 - Post Summit Report
Open-BDA Hadoop Summt 2014 - Post Summit Report
MATATABI: Cyber Threat Analysis and Defense Platform using Huge Amount of Dat...
MATATABI: Cyber Threat Analysis and Defense Platform using Huge Amount of Dat...
Open-BDA - Big Data Hadoop Developer Training 10th & 11th June
Open-BDA - Big Data Hadoop Developer Training 10th & 11th June
BigDataEurope - Big Data & Energy
BigDataEurope - Big Data & Energy
Big Data Security Intelligence and Analytics for Advanced Threat Protection
Big Data Security Intelligence and Analytics for Advanced Threat Protection
Enterprise Approach towards Cost Savings and Enterprise Agility
Enterprise Approach towards Cost Savings and Enterprise Agility
Add
Add
To Serve and Protect: Making Sense of Hadoop Security
To Serve and Protect: Making Sense of Hadoop Security
"Big Data" in the Energy Industry
"Big Data" in the Energy Industry
Generating Insight from Big Data in Energy and the Environment
Generating Insight from Big Data in Energy and the Environment
Building hadoop based big data environment
Building hadoop based big data environment
Hdp security overview
Hdp security overview
REAL-TIME BIG DATA ANALYTICAL ARCHITECTURE FOR REMOTE SENSING APPLICATION
REAL-TIME BIG DATA ANALYTICAL ARCHITECTURE FOR REMOTE SENSING APPLICATION
Smart Analytics For The Utility Sector
Smart Analytics For The Utility Sector
Building Hadoop Data Applications with Kite by Tom White
Building Hadoop Data Applications with Kite by Tom White
Demystify big data data science
Demystify big data data science
Hadoop security
Hadoop security
Big Data, Big Content, and Aligning Your Storage Strategy
Big Data, Big Content, and Aligning Your Storage Strategy
Mr. satish kumar, schnieder electric
Mr. satish kumar, schnieder electric
Similar to Big Data Security and Governance
How the latest trends in data security can help your data protection strategy...
How the latest trends in data security can help your data protection strategy...
Ulf Mattsson
Hadoop and Financial Services
Hadoop and Financial Services
Cloudera, Inc.
Time to re think our security process
Time to re think our security process
Ulf Mattsson
Comprehensive Hadoop Security for the Enterprise | Part I | Compliance Ready ...
Comprehensive Hadoop Security for the Enterprise | Part I | Compliance Ready ...
Cloudera, Inc.
Comprehensive Security for the Enterprise IV: Visibility Through a Single End...
Comprehensive Security for the Enterprise IV: Visibility Through a Single End...
Cloudera, Inc.
Security Architecture Best Practices for SaaS Applications
Security Architecture Best Practices for SaaS Applications
Techcello
Data Works Berlin 2018 - Worldpay - PCI Compliance
Data Works Berlin 2018 - Worldpay - PCI Compliance
David Walker
Not Just a necessary evil, it’s good for business: implementing PCI DSS contr...
Not Just a necessary evil, it’s good for business: implementing PCI DSS contr...
DataWorks Summit
Security and privacy of cloud data: what you need to know (Interop)
Security and privacy of cloud data: what you need to know (Interop)
Druva
Big Data Everywhere Chicago: The Big Data Imperative -- Discovering & Protect...
Big Data Everywhere Chicago: The Big Data Imperative -- Discovering & Protect...
BigDataEverywhere
Delivering User Behavior Analytics at Apache Hadoop Scale : A new perspective...
Delivering User Behavior Analytics at Apache Hadoop Scale : A new perspective...
Cloudera, Inc.
User management - the next-gen of authentication meetup 27012022
User management - the next-gen of authentication meetup 27012022
lior mazor
Don’t Get Caught in a PCI Pickle: Meet Compliance and Protect Payment Card Da...
Don’t Get Caught in a PCI Pickle: Meet Compliance and Protect Payment Card Da...
DataStax
CSA Atlanta Q1'2016 Chapter Meeting
CSA Atlanta Q1'2016 Chapter Meeting
Phil Agcaoili
Innovation Without Compromise: The Challenges of Securing Big Data
Innovation Without Compromise: The Challenges of Securing Big Data
Cloudera, Inc.
Secure Your Web Applications and Achieve Compliance
Secure Your Web Applications and Achieve Compliance
Avi Networks
Best Practices for Protecting Sensitive Data Across the Big Data Platform
Best Practices for Protecting Sensitive Data Across the Big Data Platform
MapR Technologies
Too much data and not enough analytics!
Too much data and not enough analytics!
Emma Kelly
Aligning Application Security to Compliance
Aligning Application Security to Compliance
Security Innovation
BREACHED: Data Centric Security for SAP
BREACHED: Data Centric Security for SAP
UL Transaction Security
Similar to Big Data Security and Governance
(20)
How the latest trends in data security can help your data protection strategy...
How the latest trends in data security can help your data protection strategy...
Hadoop and Financial Services
Hadoop and Financial Services
Time to re think our security process
Time to re think our security process
Comprehensive Hadoop Security for the Enterprise | Part I | Compliance Ready ...
Comprehensive Hadoop Security for the Enterprise | Part I | Compliance Ready ...
Comprehensive Security for the Enterprise IV: Visibility Through a Single End...
Comprehensive Security for the Enterprise IV: Visibility Through a Single End...
Security Architecture Best Practices for SaaS Applications
Security Architecture Best Practices for SaaS Applications
Data Works Berlin 2018 - Worldpay - PCI Compliance
Data Works Berlin 2018 - Worldpay - PCI Compliance
Not Just a necessary evil, it’s good for business: implementing PCI DSS contr...
Not Just a necessary evil, it’s good for business: implementing PCI DSS contr...
Security and privacy of cloud data: what you need to know (Interop)
Security and privacy of cloud data: what you need to know (Interop)
Big Data Everywhere Chicago: The Big Data Imperative -- Discovering & Protect...
Big Data Everywhere Chicago: The Big Data Imperative -- Discovering & Protect...
Delivering User Behavior Analytics at Apache Hadoop Scale : A new perspective...
Delivering User Behavior Analytics at Apache Hadoop Scale : A new perspective...
User management - the next-gen of authentication meetup 27012022
User management - the next-gen of authentication meetup 27012022
Don’t Get Caught in a PCI Pickle: Meet Compliance and Protect Payment Card Da...
Don’t Get Caught in a PCI Pickle: Meet Compliance and Protect Payment Card Da...
CSA Atlanta Q1'2016 Chapter Meeting
CSA Atlanta Q1'2016 Chapter Meeting
Innovation Without Compromise: The Challenges of Securing Big Data
Innovation Without Compromise: The Challenges of Securing Big Data
Secure Your Web Applications and Achieve Compliance
Secure Your Web Applications and Achieve Compliance
Best Practices for Protecting Sensitive Data Across the Big Data Platform
Best Practices for Protecting Sensitive Data Across the Big Data Platform
Too much data and not enough analytics!
Too much data and not enough analytics!
Aligning Application Security to Compliance
Aligning Application Security to Compliance
BREACHED: Data Centric Security for SAP
BREACHED: Data Centric Security for SAP
More from DataWorks Summit/Hadoop Summit
Running Apache Spark & Apache Zeppelin in Production
Running Apache Spark & Apache Zeppelin in Production
DataWorks Summit/Hadoop Summit
State of Security: Apache Spark & Apache Zeppelin
State of Security: Apache Spark & Apache Zeppelin
DataWorks Summit/Hadoop Summit
Unleashing the Power of Apache Atlas with Apache Ranger
Unleashing the Power of Apache Atlas with Apache Ranger
DataWorks Summit/Hadoop Summit
Enabling Digital Diagnostics with a Data Science Platform
Enabling Digital Diagnostics with a Data Science Platform
DataWorks Summit/Hadoop Summit
Revolutionize Text Mining with Spark and Zeppelin
Revolutionize Text Mining with Spark and Zeppelin
DataWorks Summit/Hadoop Summit
Double Your Hadoop Performance with Hortonworks SmartSense
Double Your Hadoop Performance with Hortonworks SmartSense
DataWorks Summit/Hadoop Summit
Hadoop Crash Course
Hadoop Crash Course
DataWorks Summit/Hadoop Summit
Data Science Crash Course
Data Science Crash Course
DataWorks Summit/Hadoop Summit
Apache Spark Crash Course
Apache Spark Crash Course
DataWorks Summit/Hadoop Summit
Dataflow with Apache NiFi
Dataflow with Apache NiFi
DataWorks Summit/Hadoop Summit
Schema Registry - Set you Data Free
Schema Registry - Set you Data Free
DataWorks Summit/Hadoop Summit
Building a Large-Scale, Adaptive Recommendation Engine with Apache Flink and ...
Building a Large-Scale, Adaptive Recommendation Engine with Apache Flink and ...
DataWorks Summit/Hadoop Summit
Real-Time Anomaly Detection using LSTM Auto-Encoders with Deep Learning4J on ...
Real-Time Anomaly Detection using LSTM Auto-Encoders with Deep Learning4J on ...
DataWorks Summit/Hadoop Summit
Mool - Automated Log Analysis using Data Science and ML
Mool - Automated Log Analysis using Data Science and ML
DataWorks Summit/Hadoop Summit
How Hadoop Makes the Natixis Pack More Efficient
How Hadoop Makes the Natixis Pack More Efficient
DataWorks Summit/Hadoop Summit
HBase in Practice
HBase in Practice
DataWorks Summit/Hadoop Summit
The Challenge of Driving Business Value from the Analytics of Things (AOT)
The Challenge of Driving Business Value from the Analytics of Things (AOT)
DataWorks Summit/Hadoop Summit
Breaking the 1 Million OPS/SEC Barrier in HOPS Hadoop
Breaking the 1 Million OPS/SEC Barrier in HOPS Hadoop
DataWorks Summit/Hadoop Summit
From Regulatory Process Verification to Predictive Maintenance and Beyond wit...
From Regulatory Process Verification to Predictive Maintenance and Beyond wit...
DataWorks Summit/Hadoop Summit
Backup and Disaster Recovery in Hadoop
Backup and Disaster Recovery in Hadoop
DataWorks Summit/Hadoop Summit
More from DataWorks Summit/Hadoop Summit
(20)
Running Apache Spark & Apache Zeppelin in Production
Running Apache Spark & Apache Zeppelin in Production
State of Security: Apache Spark & Apache Zeppelin
State of Security: Apache Spark & Apache Zeppelin
Unleashing the Power of Apache Atlas with Apache Ranger
Unleashing the Power of Apache Atlas with Apache Ranger
Enabling Digital Diagnostics with a Data Science Platform
Enabling Digital Diagnostics with a Data Science Platform
Revolutionize Text Mining with Spark and Zeppelin
Revolutionize Text Mining with Spark and Zeppelin
Double Your Hadoop Performance with Hortonworks SmartSense
Double Your Hadoop Performance with Hortonworks SmartSense
Hadoop Crash Course
Hadoop Crash Course
Data Science Crash Course
Data Science Crash Course
Apache Spark Crash Course
Apache Spark Crash Course
Dataflow with Apache NiFi
Dataflow with Apache NiFi
Schema Registry - Set you Data Free
Schema Registry - Set you Data Free
Building a Large-Scale, Adaptive Recommendation Engine with Apache Flink and ...
Building a Large-Scale, Adaptive Recommendation Engine with Apache Flink and ...
Real-Time Anomaly Detection using LSTM Auto-Encoders with Deep Learning4J on ...
Real-Time Anomaly Detection using LSTM Auto-Encoders with Deep Learning4J on ...
Mool - Automated Log Analysis using Data Science and ML
Mool - Automated Log Analysis using Data Science and ML
How Hadoop Makes the Natixis Pack More Efficient
How Hadoop Makes the Natixis Pack More Efficient
HBase in Practice
HBase in Practice
The Challenge of Driving Business Value from the Analytics of Things (AOT)
The Challenge of Driving Business Value from the Analytics of Things (AOT)
Breaking the 1 Million OPS/SEC Barrier in HOPS Hadoop
Breaking the 1 Million OPS/SEC Barrier in HOPS Hadoop
From Regulatory Process Verification to Predictive Maintenance and Beyond wit...
From Regulatory Process Verification to Predictive Maintenance and Beyond wit...
Backup and Disaster Recovery in Hadoop
Backup and Disaster Recovery in Hadoop
Recently uploaded
Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food Manufacturing
Pigging Solutions
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platforms
Sergiu Bodiu
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Wonjun Hwang
APIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April Automation LPDG
MarianaLemus7
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering Tips
Miki Katsuragi
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial Buildings
Memoori
Powerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time Clash
charlottematthew16
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
Rizwan Syed
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):
comworks
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
Ridwan Fadjar
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
Addepto
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Safe Software
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
2toLead Limited
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding Club
Kalema Edgar
Commit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easy
Alfredo García Lavilla
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Mark Simos
costume and set research powerpoint presentation
costume and set research powerpoint presentation
phoebematthew05
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Patryk Bandurski
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brand
gvaughan
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024
Enterprise Knowledge
Recently uploaded
(20)
Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food Manufacturing
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platforms
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
APIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April Automation LPDG
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering Tips
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial Buildings
Powerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time Clash
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding Club
Commit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easy
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
costume and set research powerpoint presentation
costume and set research powerpoint presentation
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brand
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024
Big Data Security and Governance
1.
June 30th ,
2016 Big Data Security & Governance Instilling Confidence and Trust Nick Curcuru
2.
©2016 MasterCard. Proprietary
and Confidential • Introduction to MasterCard • Security Landscape • Security Pillars • Top 10 threats: Infrastructure and Data Architecture • Hadoop Security Model • Governance and Compliance • Summary 2 Today’s Discussion
3.
©2016 MasterCard. Proprietary
and Confidential3 MasterCard – Technology & Services Payment Processing Payment Products Sponsorships Consulting Expertise Information Services Implementation Services
4.
©2016 MasterCard. Proprietary
and ConfidentialAugust 26, 20164 MasterCard helps our customers use Big Data Increasing Revenue Generation Increasing Analytic & IT Capabilities Protecting Assets Customer Centricity Monetization of data MasterCard Data Providing Hosting* Capabilities Real time interactions Improve enterprise data stewardship Reduce risk of security incident Media Measurements Journey Analytics
5.
©2016 MasterCard. Proprietary
and Confidential5 MasterCard Securing Big Data 2.2B+ GLOBAL CARDS 160MM TRANSACTIONS PER HOUR Advanced analytics are applied in a safe and secure environment finding trends and insights Card Swipes Amount, spent, time, merchant & location. Data Anonymized Analysis | Risk Detection | Customer 360 | Location selection | Customer Engagement | Economic Indicators
6.
©2016 MasterCard. Proprietary
and Confidential6 Top 5 Industries for Cyber Attacks Source: 2016 Cyber Security Intelligence Index 2015 1. Healthcare 2. Manufacturing 3. Financial Services 4. Government 5. Transportation 2014 1. Financial Services 2. Information & Communication 3. Manufacturing 4. Retail and wholesale 5. Energy and Utilities
7.
©2016 MasterCard. Proprietary
and Confidential7 Per Record Cost of a Data Breach Source : 2015 Cost of Data Breach Study:Global Analysis: Benchmark research sponsored by IBM Independently conducted by Ponemon Institute LLC, May 2015 $363 $300 $220 $215 $179 $165 $155 $137 $136 $132 $129 $127 $126 $124 $121 $68
8.
©2016 MasterCard. Proprietary
and Confidential8 Your next attacker is likely to be someone you thought you could trust Source: 2016 Cyber Security Intelligence Index
9.
©2016 MasterCard. Proprietary
and Confidential9 Top 10 Infrastructure Vulnerabilities Systems, Software, Storage Perimeter Authentication System Monitoring Testing User Authentication Applications Hardware Encryption keys Environments Shared Responsibilities Software Updates 1 2 3 4 5 6 7 8 9 10
10.
©2016 MasterCard. Proprietary
and Confidential10 Top 10 Data Architecture Vulnerabilities Data - Architecture, Governance, Management User Authentication Applications Hardware Encryption keys 1 2 3 4 User Authentication Applications Hardware Encryption keys 5 6 7 8 User Authentication Applications Hardware 9 10 11 User Authentication12
11.
©2016 MasterCard. Proprietary
and Confidential11 Nearly half of security incidents in 2015 were the result of unauthorized access Source: 2016 Cyber Security Intelligence Index Unauthorized access Malicious code Sustained probe/scan Suspicious activity Access or credentials abuse 37% 20% 20% 11% 8% 45% 29% 16% 6% 3% 2014 2015
12.
SECURITY PILLARS
13.
©2016 MasterCard. Proprietary
and Confidential13 Four Pillars of Security PERIMETER [Authenticating] VISIBILITY [Auditing] ACCESS [Authorizing] DATA [Architecting]
14.
©2016 MasterCard. Proprietary
and Confidential14 Perimeter Security – Authenticating Guarding access to the environment (cluster) Ensure your cluster: • Preserves user choice of the right Hadoop service (e.g. Impala, Spark) • Conforms to centrally managed authentication policies • Implements with existing standard systems: Active Directory and Kerberos - 1. User authenticates to Active Directory 2. Authenticated user gets Kerboros ticket 3. Ticket grants access to services
15.
©2016 MasterCard. Proprietary
and Confidential15 Access Security - Authorizing Defining user roles and their data access Outlining what data applications can use Ensure your cluster: • Defines and provides users access to data needed to do their job • Centrally manages access policies – protect all paths with strong policies moving security away from the applications • Leverages a role-based access control model built on active directory
16.
©2016 MasterCard. Proprietary
and Confidential16 Visibility Security- Auditing Reporting on where data came from and how it’s put together Ensure your cluster: • Can document where report data came from and how it was put together • Complies with policies for audit, data classification, and lineage • Centralizes the audit repository
17.
©2016 MasterCard. Proprietary
and Confidential17 Data Security – Architecting Protecting data to internal and external standards Ensure your cluster: • Controls the data analysis is performed on • Encrypts data protecting it from the root to its final destination • Applies security at the meta data level • Has well laid out encryption key management and token policies • Integrates with existing hierarchical storage management as part of key management infrastructure
18.
©2016 MasterCard. Proprietary
and Confidential18 Table stakes for big data security • Native data encryption • Security embedded in metadata • Integrated key management • Authorisation • Authentication – Multi-Factor • Strong role based access • Monitoring in real time • Audit and data lineage • Hardware-enabled security • Enterprise Identity management integration
19.
©2016 MasterCard. Proprietary
and Confidential19 Best practices People and Process • Segregation of Duties • Segregation of Data Access • Continuous knowledge transfer, training and awareness • Process documentation – controls, response and continuity planning Technology • Strong Authentication & Authorization • Real Time Monitoring • Regular Penetration Testing
20.
©2016 MasterCard. Proprietary
and Confidential20 Lessons learned • Emphasize Hadoop isn’t one thing, but a “collection of things” • Education & documentation is 60% of the effort • Explain why Hadoop isn’t a database so don’t expect similar controls • Security is neither quick nor easy • Big Data technology is still maturing • Close collaboration with your partners is critical • Security is continuous not a check in the box
21.
What to do
22.
©2016 MasterCard. Proprietary
and Confidential22 Where to Start 1. Assess security maturity over three dimension: – People, Process and Technology 2. Classify data into categories – Personally Identifiable, Health Data, Payment Related, Analysis 3. Start real time system and data monitoring 4. Take inventory of current Hadoop system security capabilities – Refer to security table stakes and identify gaps 5. Identify training needs – Business, Technology and Third Party Partners
23.
©2016 MasterCard. Proprietary
and Confidential23 Start with the Hadoop Security Maturity Pilot: Data Free-for-All: Available & Error-Prone Basic Security Controls: • Authorization • Authentication • Auditing Data Security & Governance: • Lineage Visibility • Metadata Discovery • Encryption & Key Management Regularoty Compliance Audit-Ready & Protected Security enforcement for all data-at-rest and data-in- motion • Full encryption • Encryption management • Token system management • Transparency • Real time monitoring • Element level security DataVolume&Sensitivity Security Compliance & Risk Mitigation Highly Vulnerable Data at Risk Reduced Risk Exposure Managed, Secure, Protected Enterprise Data Hub Secure Data Vault 0 1 2 3
24.
©2016 MasterCard. Proprietary
and Confidential24 Transparent Encryption & Key Management Protection for all data: • Structured and unstructured • Metadata, temp files and log files Data-at-rest encryption options: • HDFS Encryption for the data • Encryption for: metadata – log files Yarn – Resource Manager Data Management Layer Impala Hive HDFS HBase Apache Sentry SSL Certificates and SSH Keys Log/Config/Spill filesHSM
25.
©2016 MasterCard. Proprietary
and Confidential Look at Apache Atlas Source: Apache Software Foundation and Hortonworks Features • Data Classification • Metadata • Centralized Auditing • Search & Lineage (Browse) • Security & Policy Engine
26.
©2016 MasterCard. Proprietary
and Confidential Compliance and Governance Compliance Evolution Integrity Stewardship Ethics Specific • Taxonomy • Transparency • Auditability • Consistency • Accountability • Checks-and- Balances • Standards Governance Controls Guardian
27.
©2016 MasterCard. Proprietary
and Confidential27 Summary • 60 % of threats are from inside the organization • Security is applied end to end in the process • Access: People, Process and Technology in your security strategy • Hadoop is still maturing • Governance includes data usage • Don’t confuse compliance with security
28.
QUESTIONS
29.
©2016 MasterCard. Proprietary
and Confidential Contact Us 29 Nick Curcuru +1 (914) 413 3822 Nick.Curcuru@mastercard.com
30.
BONUS SLIDES
31.
©2016 MasterCard. Proprietary
and Confidential31 Top 10 Infrastructure Vulnerabilities Perimeter Authentication System Monitoring Testing User Authentication Applications Hardware Encryption keys Environments Shared Responsibilities Software Updates 1 2 3 4 5 6 7 8 9 10
32.
©2016 MasterCard. Proprietary
and Confidential32 Points of Attack- Infrastructure Threat Only password credentials for authentication to environment Applications controls data access Database and application servers are the same hardware Users authenticate with generic/ shared/ application ID Weakness Mitigation Perimeter Authentication Access to data is at the system level and at the data element (fine-grained) User authentication Applications Hardware Encryption Keys Encryption keys are not rotated. Use two-factor authentication: tokens, RSA or Biometric technology Credentials should never be shared: each user and application should have unique/non-shared credentials to host systems Separate database and application servers – isolates attack vectors Set up periodic rotation of encryption 1 2 3 4 5
33.
©2016 MasterCard. Proprietary
and Confidential33 Points of Attack- Infrastructure Threat Insecure/uncertified environments have direct access to secure/certified environments. Patches or upgrades do not happen on a regular release cycle to ensure the system is protected from software vulnerabilities. Platform not monitored on continual basis setting up reactive posture: after the fact Systems admin, DBA, application developer, and web admin responsibilities are shared Weakness Mitigation Environments Set up release schedule, hold software vendors to security standards & verify standards are met Shared Responsibilities Software Updates System Monitoring Testing Infrequent penetration tests and application security scans Segregate systems. Systems with access to each other need the same levels of security and controls Divide responsibilities implement role based access and controls Set up constant monitoring of environment using data driven alert Develop penetration testing schedule and remediation review quarterly 6 7 8 9 10
34.
©2016 MasterCard. Proprietary
and Confidential34 Top 10 Data Architecture Vulnerabilities User Authentication Applications Hardware Encryption keys 1 2 3 4 User Authentication Applications Hardware Encryption keys 5 6 7 8 User Authentication Applications Hardware 9 10 11 User Authentication12
35.
©2016 MasterCard. Proprietary
and Confidential35 Points of Attack-Enterprise Information Management Threat Sensitive data - encrypted /tokenized /hashed is comingled with non- sensitive data Users have access to data they should not, or access to data that is unnecessary Encryption Keys stored with the data they encrypt. Reliant on applications to control access to data and enforce data security standards Weakness Mitigation Co-mingling of data Use role based access control - Apply fine-grained data access controls Applications Access Controls Key Storage Data Movement Sensitive data is not encrypted on disk/at-rest or on the wire motion. Use physical or logical separation between data types. Apply security at the table, field and element level, as well as application level Store encryption keys in a spate location away from data and limit access through control processes Encrypt all sensitive data on disk/at-rest or on the wire motion. 1 2 3 4 5 Access
36.
©2016 MasterCard. Proprietary
and Confidential36 Points of Attack-Enterprise Information Management Threat Security and operational configurations are not documented or reviewed regularly Little to no governance standards and rules exist if they do they are focused on data quality Information security response and business continuity plan does not exist or is not reviewed/exercised on a regular basis Sensitive data is written to systems logs in an unprotected form Weakness Mitigation Security & Operational Configurations Document standards, set up review cycle at minimum yearly and include data usage as part of the standards Data Logs Governance standards Response & Business Continuity Plans Data Usage Monitoring Data usage either not monitored on continual basis or is buried in logs with no one looking at them Document all configurations, develop audit trail for changes, review configurations yearly Metadata carries security throughout the data trail and enables enforcement Yearly review and revision of each plan using a cross functional team: Infosec, IT, Operations, Legal Set automated thresholds and measurements using data to drive exception alerts 6 7 8 9 10 Data - Architecture, Governance, Management
Download now