Protecting Your Data in the Cloud - CSO - Conference 2011
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This document discusses protecting data in the cloud and introduces Ulf Mattsson, the Chief Technology Officer of Protegrity. It summarizes guidance from the Cloud Security Alliance on cloud security risks and debates encryption versus tokenization approaches. Protegrity offers data security software that uses patented tokenization technology to help organizations comply with privacy regulations and prevent data breaches in a cost effective manner. Tokenization can significantly reduce the risks of storing sensitive data in the cloud.
![P r o t e c t i n g Yo u r D a t a i n t h e
C lo u d
Ulf Mattsson
Chief Technology Officer
ulf.mattsson [at] protegrity.com](https://image.slidesharecdn.com/csochicago2011-ulfmattsson-120518154233-phpapp02/85/Protecting-Your-Data-in-the-Cloud-CSO-Conference-2011-1-320.jpg)
![Please contact me for more information
ulf.mattsson [at] protegrity.com
Visit our table](https://image.slidesharecdn.com/csochicago2011-ulfmattsson-120518154233-phpapp02/85/Protecting-Your-Data-in-the-Cloud-CSO-Conference-2011-27-320.jpg)
Protecting Your Data in the Cloud - CSO - Conference 2011
- 1. P r o t e c t i n g Yo u r D a t a i n t h e C lo u d Ulf Mattsson Chief Technology Officer ulf.mattsson [at] protegrity.com
- 2. Ulf Mattsson 20 years with IBM Development & Global Services Inventor of 22 patents – Encryption and Tokenization Co-founder of Protegrity (Data Security) Research member of the International Federation for Information Processing (IFIP) WG 11.3 Data and Application Security Member of • Cloud Security Alliance (CSA) • PCI Security Standards Council (PCI SSC) • American National Standards Institute (ANSI) X9 • Information Systems Security Association (ISSA) • Information Systems Audit and Control Association (ISACA) 2
- 3. Guidance from Cloud Security Alliance 3
- 5. About Protegrity Proven enterprise data security software and innovation leader • Sole focus on the protection of data • Patented Technology, Continuing to Drive Innovation Growth driven by compliance and risk management • PCI (Payment Card Industry) • PII (Personally Identifiable Information) • PHI (Protected Health Information) – HIPAA • State and Foreign Privacy Laws, Breach Notification Laws • High Cost of Information Breach ($4.8m average cost), immeasurable costs of brand damage , loss of customers • Requirements to eliminate the threat of data breach and non-compliance Cross-industry applicability • Retail, Hospitality, Travel and Transportation • Financial Services, Insurance, Banking • Healthcare • Telecommunications, Media and Entertainment • Manufacturing and Government 5
- 6. Risks Associated with Cloud Computing % Source: The evolving role of IT managers and CIOs Findings from the 2010 IBM Global IT Risk Study 6
- 7. Best Source of Incident Data “It is fascinating that the top threat events in both 2010 and 2011 are the same and involve external agents hacking and installing malware to compromise the confidentiality and integrity of servers.” Source: 2011 Data Breach Investigations Report, Verizon Business RISK team Source: Securosis, http:/ securosis.com/ / 7
- 8. Data Breaches – Mainly Online Data Records 900+ breaches 900+ million compromised records: % Source: 2010 Data Breach Investigations Report, Verizon Business RISK team and USSS 8
- 9. Compromised Data Types - # Records % Source: Data Breach Investigations Report, Verizon Business RISK team and USSS 9
- 10. Industry Groups Represented - # Breaches % Source: Data Breach Investigations Report, Verizon Business RISK team and USSS 10
- 11. Breach Discovery Methods - # Breaches % Source: Data Breach Investigations Report, Verizon Business RISK team and USSS 11
- 12. Example of How the Problem is Occurring – PCI DSS Encrypt Data on Attacker Public SSL Public Network Networks (PCI DSS) Private Network Clear Text Data Application Clear Text Data Database Encrypt Data OS File System At Rest (PCI DSS) Storage System Source: PCI Security Standards Council, 2011 12
- 13. How can the problem be solved? -Tokenization and other options can reduce the risk Source: PCI Security Standards Council, 2011 13
- 14. Amazon Cloud & PCI DSS Just because AWS is certified doesn't mean you are • You still need to deploy a PCI compliant application/service and anything on AWS is still within your assessment scope PCI-DSS 2.0 doesn't address multi-tenancy concerns You can store PAN data on S3, but it still needs to be encrypted in accordance with PCI-DSS requirements • Amazon doesn't do this for you • You need to implement key management, rotation, logging, etc. If you deploy a server instance in EC2 it still needs to be assessed by your QSA (PCI auditor) • Organization's assessment scope isn't necessarily reduced Tokenization can reduce your handling of PAN data Source: Securosis, http:/ securosis.com/ / 14
- 15. Tokenization Use Case Example A leading retail chain • 1500 locations in the U.S. market Simplify PCI Compliance • 98% of Use Cases out of audit scope • Ease of install (had 18 PCI initiatives at one time) Tokenization solution was implemented in 2 weeks • Reduced PCI Audit from 7 months to 3 months • No 3rd Party code modifications • Proved to be the best performance option • 700,000 transactions per days • 50 million card holder data records • Conversion took 90 minutes (plan was 30 days) • Next step – tokenization server at 1500 locations 15
- 16. What is Tokenization and what is the Benefit? Tokenization • Tokenization is process that replaces sensitive data in systems with inert data called tokens which have no value to the thief. • Tokens resemble the original data in data type and length Benefit • Greatly improved transparency to systems and processes that need to be protected Result • Reduced remediation • Reduced need for key management • Reduce the points of attacks • Reduce the PCI DSS audit costs for retail scenarios 16
- 17. Token Flexibility for Different Categories of Data Type of Data Input Token Comment Token Properties Credit Card 3872 3789 1620 3675 8278 2789 2990 2789 Numeric Medical ID 29M2009ID 497HF390D Alpha-Numeric Date 10/30/1955 12/25/2034 Date E-mail Address bob.hope@protegrity.com empo.snaugs@svtiensnni.snk Alpha Numeric, delimiters in input preserved SSN delimiters 075-67-2278 287-38-2567 Numeric, delimiters in input Credit Card 3872 3789 1620 3675 8278 2789 2990 3675 Numeric, Last 4 digits exposed Policy Masking Credit Card 3872 3789 1620 3675 clear, encrypted, tokenized at rest Presentation Mask: Expose 1st 3872 37## #### #### 6 digits 17
- 18. Data Tokenization – Reducing the Attack Surface Security 12 3 4 5 6 12 3 4 5 6 12 3 4 12 3 4 5 6 9 9 9 9 9 9 12 3 4 12 3 4 5 6 12 3 4 5 6 12 3 4 Admin User User User Tokenization Tokenization Server Server Application Databases 12 3 4 5 6 9 9 9 9 9 9 12 3 4 12 3 4 5 6 9 9 9 9 9 9 12 3 12 3 4 5 6 9 9 9 9 9 9 12 3 4 4 : Data Token U n p r o t e c t e d s e n s it iv e in f o r m a t io n : 18 P r o t e c t e d s e n s it iv e
- 19. PCI DSS - Ways to Render the PAN Unreadable Two-way cryptography with associated key management processes One-way cryptographic hash functions Index tokens and pads Truncation (or masking – xxxxxx xxxxxx 6781) 19
- 20. Positioning Different Protection Options Evaluation Criteria Strong Formatted Tokens Encryption Encryption Security & Compliance Total Cost of Ownership Use of Encoded Data Best Worst 20
- 21. Different Approaches for Tokenization Traditional Tokenization • Dynamic Model or Pre-Generated Model • 5 tokens per second - 5000 tokenizations per second Protegrity Next Generation Tokenization • Memory-tokenization • 200,000 - 9,000,000+ tokenizations per second • “The tokenization scheme offers excellent security, since it is based on fully randomized tables.” * • “This is a fully distributed tokenization approach with no need for synchronization and there is no risk for collisions.“ * *: Prof. Dr. Ir. Bart Preneel, Katholieke University Leuven, Belgium 21
- 22. Tokenization Summary Traditional Tokenization Protegrity Tokenization Footprint Large, Expanding. Small, Static. The large and expanding footprint of Traditional The small static footprint is the enabling factor that Tokenization is it’s Achilles heal. It is the source of delivers extreme performance, scalability, and poor performance, scalability, and limitations on its expanded use. expanded use. High Complex replication required. No replication required. Availability, Deploying more than one token server for the Any number of token servers can be deployed without DR, and purpose of high availability or scalability will require the need for replication or synchronization between the Distribution complex and expensive replication or servers. This delivers a simple, elegant, yet powerful synchronization between the servers. solution. Reliability Prone to collisions. No collisions. The synchronization and replication required to Protegrity Tokenizations’ lack of need for replication or support many deployed token servers is prone to synchronization eliminates the potential for collisions . collisions, a characteristic that severely limits the usability of traditional tokenization. Performance, Will adversely impact performance & scalability. Little or no latency. Fastest industry tokenization. Latency, and The large footprint severely limits the ability to place The small footprint enables the token server to be Scalability the token server close to the data. The distance placed close to the data to reduce latency. When between the data and the token server creates placed in-memory, it eliminates latency and delivers the latency that adversely effects performance and fastest tokenization in the industry. scalability to the extent that some use cases are not possible. Extendibility Practically impossible. Unlimited Tokenization Capability. Based on all the issues inherent in Traditional Protegrity Tokenization can be used to tokenize many Tokenization of a single data category, tokenizing data categories with minimal or no impact on footprint more data categories may be impractical. or performance. 22
- 23. Evaluating Encryption & Tokenization Approaches Evaluation Criteria Encryption Tokenization Database Database Traditional Memory Area Impact File Column Tokenization Tokenization Encryption Encryption (Protegrity) Availability Scalability Latency CPU Consumption Data Flow Protection Compliance Scoping Security Key Management Data Collisions Separation of Duties Best Worst 23
- 24. Data Protection Challenges The actual protection of the data is not the challenge Centralized solutions are needed to managed complex security requirements • Based on Security Policies with Transparent Key management • Many methods to secure the data • Auditing, Monitoring and Reporting Solutions that minimize the impact on business operations • Highest level of performance and transparency Rapid Deployment Affordable with low TCO Enable & Maintaining compliance 24
- 25. Protegrity Data Security Management Policy File System Protector Database Protector Audit Log Application Protector Enterprise Data Security Administrator Tokenization Secure Server Archive : Encryption service 25
- 26. Protegrity Data Protection Platform Coverage • Supports heterogeneous environments across operating systems, applications, file systems and databases Protection Methods • Encryption, Tokenization, DTP2 (data type/format preserving encryption), Masking and Monitoring Packaged Data Protectors for Databases, Files and Applications Next Generation Tokenization Separation of Duties/Roles • IT Security resource responsible for defining policy is different than Administrator’s managing the sensitive data Policy and Key Management • Central and secure solution to manage the keys to the data across the enterprise Central Reporting • Reporting for security management compliance assessment 26
- 27. Please contact me for more information ulf.mattsson [at] protegrity.com Visit our table
Editor's Notes
- #2: 05/18/12