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DSAC (Digital Signature Aggregation and Chaining)

DSAC (Digital Signature Aggregation and Chaining). Digital Signature Aggregation & Chaining An approach to ensure integrity of outsourced databases. Contents. Signature Aggregation Mechanisms Chaining Mechanism Comparison of the results with previous work. ODB.

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DSAC (Digital Signature Aggregation and Chaining)

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  1. DSAC(Digital Signature Aggregation and Chaining) Digital Signature Aggregation & Chaining An approach to ensure integrity of outsourced databases

  2. Contents • Signature Aggregation Mechanisms • Chaining Mechanism • Comparison of the results with previous work

  3. ODB • Outsourced Data Base(ODB) model : Client stores its data at an external data base service provider. • Concern: Ensure the database security & integrity.

  4. Authenticity: The tuples in the result set have not been tampered i.e correctness. • Integrity: No valid tuples have been omitted from the result set i.e completeness

  5. Size of a result set & VO • 0-n, or 2^n subsets, where, n is total number of tuples in the database. Verification Object (VO) : Is the result set including the tuples and verification signatures.

  6. Merkle Hash Tree • Use to prove existence of an element in a set. For eg. prove x1 exists in the set y={x2, x6, x1, x9} • Constructed as binary tree where leaves are hash value of corresponding element. • Non leaf & Leaf nodes • Root of the MHT is digitally signed using public key signature scheme (RSA/ DSA)

  7. MHT example…

  8. Auth DS (Authenticated Data Structures) • Approach to prove correctness • Uses MHT to prove correctness of the result set. • Limitation : Need to pre-compute and store a potentially large number of authenticated data structures to answer queries. • Completeness issue not answered

  9. VB Tree Approach • Uses a modified MHT • Not only root of MHT is signed but all nodes as well • Limitation: Consumes large storage space and increased verification time. • Provides proof of correctness • Completeness issue not answered !

  10. Drawbacks… • Overheads associated with building, storing and updating data structures in AuthDS and VB tree. • Signs each individual tuple before storing. • Server stores tuples along with its corresponding signature. • In response to a query, server sends both tuple and its signature.

  11. Drawbacks(contd.) • Query reply set consists of thousands of tuples. • Sending/ receiving and verifying signature of each tuple. • Expensive for the querier.

  12. DSAC • Combines multiple individual signatures in the result set into a unified/ aggregated signature. • Verifying a unified signature is same as verifying signatures of each individual tuple in the result set.

  13. Completeness • Includes the boundary tuples as well to ensure all the tuples matching the query is returned. • Link the tuple level signatures to form a signature chain.

  14. Constructing signature chains • If h() is a hash function such as SHA, • || denotes concatenation, • IPRi denotes immediate predecessor tuple along dimension ‘i’ , • l being number of searchable dimensions, • SK is private signing key of the data owner

  15. then the signature of a tuple ‘r’ can be computed as follows

  16. Computing IPR of a tuple • Sort tuple in increasing order of the attribute value for each dimension. • IPR of a given tuple in a given dimension is a tuple with highest value of the attribute that is less than the value of that tuple. • Each tuple has as many IPRs as the number of searchable dimensions.

  17. Example of signature chaining • Consider tuple R5

  18. Completeness (contd.) • In this way, server answers range queries by releasing all matching tuples, boundary tuples as well as aggregated signature. • Signature chain proves querier that server has returned all tuples in the query range proving completeness.

  19. Compleness(contd.) • Querier on receiving the result set: • Verifies the values in boundary tuples are just beyond the query range. • This ensures completeness for the querier.

  20. Analysis of DSAC scheme • We compare the DSAC scheme with other prominent correctness/ completeness guarantee schemes such as AuthDS and VB tree.

  21. Query Verification Time (Naïve approach vs DSAC)

  22. VO Size (Naïve approach vs DSAC approach)

  23. Freshness • Freshness : The result set in response to a query should be the recent snapshot of the database. • Prevents the server from replaying the old signature chains, hence freshness is part of data integrity concerns.

  24. Conclusion • Developed a new approach DSAC to ensure integrity and authentication of the result set. • Completeness guaranteed, which no other works has been able to. • Experimenting and comparing the results with other works like AuthDS and VB tree approaches.

  25. Further scope • How to reduce the size of the verification object.

  26. Reference • DSAC : An approach to ensure integrity of outsourced databases using signature aggregation and chaining • Authors : Maithili Narasimha & Gene Tsudik Computer Science Department University of California, Irvine

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