Database Laboratory Regular Seminar 2013-07-22 TaeHoon Kim

1. Article New Approaches to Security and Availability for Cloud Data Ari Juels, AlinaOprea Communications of ACM Feb. 2013 Database Laboratory Regular Seminar 2013-07-22 TaeHoonKim

2. Contents • Introduction • Solution Overview • Iris - Iris Authenticated file system - Iris Structure • Auditing Framework • Conclusion

3. 1. Introduction • Cloud Computing Service Model offers users(called tenants) on-demand network access • A large shared pool of computing resources(cloud) • Many of company adopted private cloud • IBM, HP, VMware, EMC2 • Public cloud are not adopted • Security and operational risk • Including hardware failure, software bugs, power outages, server misconfiguration, malware, and inside threats • Lack of availability and reliability • Striking loss of personal customer data • http://blog.naver.com/PostView.nhn?blogId=lugenzhe&logNo=90100646811&redirect=Dlog&widgetTypeCall=true

4. 1. Introduction • Potentially malicious tenants • Ristenpart et al,[18], such an attacker an exploit side channels in shared hardware to exfiltrate sensitive data • Our research addresses • The challenge of migrating enterprise data into the public cloud • Devised Cryptographic protocol • Propose auditing framework to verify properties of the internal operation of the cloud and assure enterprise

5. 2. Solution Overview • Our vision of more-trustworthy cloud-computing model • Manages cryptographic keys • Maintains trusted storage for integrity • Freshness enforcement • Redundancy to data for enhanced availability

6. 3. Iris Authenticated file system • An authenticated file system • Allows migration of existing internal enterprise systems into cloud • Offer strong integrity and freshness guarantees • Minimizes the effects of network latency on file-system operations • Is designed to use any existing back-end cloud storage system transparently without modification

7. 3. Iris Structure(2 layers) • The gateway-side • Caches data and meta-data blocks from the file system recently accessed by enterprise users. • Computes integrity checks • Namely MACs on data block • MACs • Fixed-size file segments of typical size 4KB • Enables random access • Verification of individual file-block integrity

8. 3. Iris Structure(2 layers) • Merkle-tree-based structure • Internal nodes of the tree contain hashes of their children • Tenant can efficiently verify the integrity and freshness data MAC and freshness of the block-version number • Support for existing file-system operations • Support for concurrent operations • http://en.wikipedia.org/wiki/Merkle_tree#How_hash_trees_work

9. 4. Auditing Framework • When Alice(client) stores data with Bob, she wants to know that Bob(service provider) has not let her data succumb to bit rot, storage-device failure, corruption by buggy software, … etc • Using strong cryptographic approach to assurance : PoR(Proofs of Retrievability) • Bob proves to Alice that a given piece of Data D stored in the cloud is not damaged and retrievable • Cryptographically verify the correctness of all cloud-stored data

10. 4. Auditing Framework • Notation • D is some piece of data • D* is constructed by appending what are called “parity blocks” • ri denote the ith data block(fixed-size 4KB) • Using secret key k, Alice can compute MACs, secret-key digital signatures over data blocks r1, r2, r3 … rn • To verify the correctness of a block r1, Alice uses k and ci • Alice needs to store only the key k • http://en.wikipedia.org/wiki/Merkle_tree#How_hash_trees_work

11. 4. Auditing Framework • PoR(Proofs of Retrievability) • efficient only for checks on static data(such as archived data) • PDP(Proof of Data Possession) • Enables public verification of data integrity • Dynamic PoR • Conceals individual parity-block updates from Bob, as well as the code structure • PoS(Proofs of Storage) • Detecting data loss • E.g)drive crash, a large data center is likely to experience thousands of drive failures each year[19]

12. 4. Auditing Framework • Auditing of drive-failure Solution : RAFT(Remote Assessment of Fault Tolerance • Makes use of bounds on the seek time of a rotational drive • RAFT operates specifically on data stored in rotational drives, exploiting their performance limitations as a bounding parameter

13. 4. Auditing Framework • If the cloud provider fails to respond correctly to an audit due to data loss? • HAIL(High availability and integrity layer) is the solution • Works by promptly detecting and recovering from data corruption(is similar to RAID) • HAIL • An extension of RAID into the cloud • distributing data across multiple cloud providers to achieve continuous availability • http://blog.naver.com/capemay?Redirect=Log&logNo=40192616466 • http://jaesoo.com/study_board/23324

14. 4. Auditing Framework • To provide recovery(resilience)cloud-provider failure, the gateway splits the data into fixed-size blocks and encodes it with a new erasure code ; dispersal code • Distributes her data with embedded redundancy • a set of n cloud providers:S1 … Sn

15. Conclusion • Described new techniques • a range of protections, integrity and freshness verification to high data availability • Proposed an auditing framework • These technique enable an extension from enterprise internal data centers into public clouds • Our hope • alleviate some of the concern over securityin the cloud • facilitate migration of enterprise resources into public clouds

16. Q/A • Thank you for listening my presentation