1. UT DALLAS Erik Jonsson School of Engineering & Computer Science FEARLESS engineering BigSecret: A Secure Data Management Framework for Key-Value Stores Erman Pattuk Murat Kantarcioglu Vaibhav Khadilkar Huseyin Ulusoy Sharad Mehrotra (Univ. of California at Irvine)

2. FEARLESS engineering Introduction Increasing amount of internet usage –Number of active users –Number of transactions per unit time –Size of the stored data –A new concept: BigData Existing techniques failed to satisfy new requirements To cope with BigData, Key-Value Stores emerge as a popular option –Efficiency and Scalability

3. FEARLESS engineering Introduction Amazon SimpleDB Google BigTable Microsoft Azure … KeyValue pattuk_erman:bank1919381 pattuk_erman:ssn1928319 ulusoy_huseyin:bank4476861 ulusoy_huseyin:ssn1148793

4. FEARLESS engineering Proposed Framework: BigSecret Public Private Amazon SimpleDB Google BigTable Microsoft Azure … BigSecret Dept 1 Dept 2

5. FEARLESS engineering Outline Partitioning data among multiple cloud providers Storing data on a provider, while protecting efficiency and privacy Querying outsourced data Experiments

6. FEARLESS engineering Data and Workload Sharing BigSecret Data Owner Provider-1 Provider-2 Provider-3 Constraints

7. FEARLESS engineering Constraints in Partitioning BigSecret Provider-1 Provider-2 Provider-N … Monetary Cost < 10 Security Disclosure < 5% Optimize Execution Time 10% Data 20% Workload 20% Data 10% Workload 15% Data 13% Workload

8. FEARLESS engineering Storing Data in Secure Form Transform data using Encryption Models

9. FEARLESS engineering Query Execution BigSecret Provider-1 GET: “John” – “traits” – “height” GET: A12C04 – BF2139 – 51231D RESULT: 1295DC10 RESULT: “170 cm”

10. FEARLESS engineering Experiments Performed experiments using Yahoo! Cloud Serving Benchmark Created tables consisting of 1,2,4,8,16, and 32 Millions of rows –Each row has 10 Key-Value entries of 100B Created 3 different workloads –1K queries for single-cloud experiments –100K queries for multi-cloud experiments

11. FEARLESS engineering Single-Cloud Experiments Workload – 1 (Get intensive)

12. FEARLESS engineering Single-Cloud Experiments Workload – 2 (Put intensive)

13. FEARLESS engineering Single-Cloud Experiments Workload – 3 (Scan intensive)

14. FEARLESS engineering Multi-Cloud Experiments Provider Properties Provider 1Provider 2 StoragePlaintextModel-1 Risk weight10.7 SpeedFastSlow Monetary cost$700$3700 Sensitivity disclosure risk %100%70

15. FEARLESS engineering Multi-Cloud Experiments Workload – 3 (Scan intensive)

16. FEARLESS engineering Conclusion If Scan is needed, Model-1 can be used –Otherwise, it’s not so efficient –May use other techniques to support Scan Model-2 and 3 perform well with minor overhead We plan to add support for other Key-Value stores BigSecret is open source –https://github.com/ermanpattuk/BigSecret

17. FEARLESS engineering Q&A Thank You