1. Data Integrity Proofs in Cloud Storage Author: Sravan Kumar R and Ashutosh Saxena. Source: The Third International Conference on Communication Systems and Networks (COMSNETS), 2011, Bangalore, India, pp. 1–4. Presenter: Tsuei-Hung Sun ( 孫翠鴻 ) Date: 2011/3/4

2. Outline Introduction Motivation Scheme Performance Evaluation Advantage vs. Drawback Comment

3. Introduction(1/3) Data outsourcing to cloud storage server –Data Authentication –Data Integrity Proof of retrievability (POR) –Obtain and verify data is not modified. –Using a keyed hash function h K (F). –Prevent the cloud storage archives modifying the data without the consent of the data owner. H(.): hash function K: Secret Key F: File

4. Introduction(2/3) Drawback of POR –It need high resource cost for the implementation. –It need to store secret key and hash value as many as file that stored at server. –It is a burdensome for server and some device.

5. Introduction(3/3) Proof of retrievability for large files using “sentinels.” –Only a single key can be used. –Access only a small portion of the file F. –Setup phase: Randomly embeds sentinels among the data blocks. –Verification phase: Verifier check the integrity of the data file F by challenge prover specifies positions and asking return the associated sentinel values. A. Juels and B. S. Kaliski, Jr., “Pors: proofs of retrievability for large files,” Proceedings of the 14th ACM conference on Computer and communications security, New York, USA, 2007, pp. 584–597.

6. Motivation The improve scheme need to insert sentinels and error correcting codes. The improve scheme need to store all sentinels. In the future, the owner of data maybe a small device (ex. PDA, mobile phone) Goal –Deal with the problem of implementing POR. –Proof without the need to access the entire file or client to retrieving the entire file from the server. –Minimizing the local computation and bandwidth consumed at the client.

7. Scheme(1/4) Assumption and Limit –Storage server might not be malicious. –The proof of data integrity protocol just checks the integrity of data. –Only apply to static storage of data. –The number of queries that can be asked by the client is fixed.

8. Scheme(2/4) Setup phase –Let file F consist of n blocks and create metadata to append on it. –Let each of n data blocks have m bits in them. Fig. A data file F with 6 data blocks.

9. Scheme(3/4) Setup phase (cont.) 1. Generation of meta-data  2. Encrypting the meta data  3. Appending of meta data k: The number of bits per data block which read as meta data. g: a function to generates a set of k bit positions. h: a function to generates a k bit integer α i for each i. M i : a encrypted m i by h.

10. Scheme(4/4) Verification phase Verifier (Client)Archive (Cloud) Challenges g(i,j) Using g(i,j) to find the corresponding meta data. k+1 bits Using α i to decrypt Compare decrypted bits and send by cloud bits

11. Performance Evaluation Storing only a single cryptographic key and two functions which using to generate a random sequence. Only encrypting a part of file, so it can save computational time of the client. Using XOR to instead hash function is more efficient. Verification just need to find and send few bits of data to the client. Network bandwidth is very less (k+1 bits for one proof).

12. Advantage vs. Drawback Advantage –Reducing the computational and storage overhead of the client. –Minimizing the computational overhead of the cloud. –Reducing the network bandwidth consumption. –It is advantageous to thin clients. Drawback –It not prevent the archive from modifying the data.

13. Comment The decryption and comparison are not very clear to check that the response is correct or not. It still need to store α i as many as number of files.