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Searchable Symmetric Encryption: Improved Definitions and Efficient Constructions

Explore improved definitions and efficient constructions for Searchable Symmetric Encryption. Learn about SSE security notions, constructions, and privacy-preserving search techniques on encrypted data.

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Searchable Symmetric Encryption: Improved Definitions and Efficient Constructions

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  1. Searchable Symmetric Encryption: Improved Definitions and Efficient Constructions • Reza Curtmola Juan Garay Seny Kamara Rafail Ostrovsky • Johns Hopkins Bell Labs Johns Hopkins UCLA

  2. Remote Storage • Remote storage is ubiquitous • data backups • GMail, Yahoo Mail etc... • Q: How do we store sensitive data on an untrusted server? • A: Encryption • hides all partial information about data • client must download all data, decrypt and perform operations locally • Can we enable the server to help ?

  3. Outline • Motivation • Brief overview of different models for private searching • Our focus: Searchable Symmetric Encryption (SSE) • Revisiting security definitions for SSE • point out subtle (but serious) issues with previous definitions • Two new notions of security for SSE • “Non-adaptive” security • “Adaptive” security • Two new constructions • Extensions

  4. Private Searching • MPC: general, but inefficient [Yao82, GMW87, BGW88, CCD88] • Searching (explicitly) -- different settings • public data: unencrypted (e.g., stock-quotes, news articles) • client wishes to hide which element is accessed • PIR and its variants [CGKS,KO97,...] • user-owned data: symmetrically encrypted • client can upload additional “encrypted” data structures to help search • Oblivious RAMs, searchable symmetric encryption [O90, OG96, SWP00, Goh03, CM05] • third-party data: public-key encrypted • data comes encrypted to server from users other than client [BKOS07] • public-key searchable encryption [BDOP05,BW06...]

  5. Searchable Symmetric Encryption • We consider the following scenario • client has a collection of documents that consists of a set of words • encrypts document collection together with additional data structure • sends everything to server • Functionality: server should support the following types of queries • find all documents that contain a particular keyword • Privacy: allow server to help, but reveal as little as possible

  6. Prior work on SSE • SSE can be achieved using oblivious RAMs [Ost, GO] • functionality: can simulate any data structure in a hidden way, and can support conjunctive queries, B-trees etc... • privacy: hides everything, even the accesspattern • efficiency: logarithmic number of rounds per each read/write • Q: Can we search over encrypted data in single/constant rounds? • with absolute privacy, recently solved by Boneh-Kushilevitz-Ostrovsky-Skeith wish sqrt{DB} communication. • This paper: what if we relax the security requirements to get better performance?

  7. How do we relax the security definition ? • Informal answer • leak the access pattern but nothing else • What does it mean to “leak the access pattern but nothing else” ? • defining this formally is “delicate” • in fact, there are issues with 3 previous attempts

  8. Constant-round SSE with relaxed security • 3 previous constant-round solutions that “leak access pattern” • “Practical techniques for searches on encrypted data” [SWP00] • “Secure Indexes” [Goh03] • “Privacy-preserving keyword searches on remote encrypted data” [CM05] • [BKOS-07] is constant round but sqrt(DB) communication

  9. Outline • Motivation • Overview of privacy-preserving searching • Searchable symmetric encryption • Revisiting security definitions for SSE • “Non-adaptive” definitions and construction • “Adaptive” definitions and construction • Extensions

  10. Revisiting SSE security definitions • [SWP00,Goh03,CM05]: “A secure SSE scheme should not leak anything beyond the outcome of a search” • “search outcome”: memory addresses of documents that contain a hidden keyword (precise definition later) • Important to note: different keyword requests may lead to the same search outcome • “search pattern”: whether two queries were for the same keyword or not • A (slightly) better intuition • “A secure SSE scheme should not leak anything beyond the outcome and the pattern of a search”

  11. Issues with SWP’s security definition • [SWP00] implicitly use indistinguishability [GM84] as a security definition • “any function of the plaintext that can be computed from the ciphertext can be computed from the length of the plaintext” • Issue: adversary gets to see search outcomes and search pattern • [SWP00] does not model the fact that this additional information is revealed. • There are also issues with definitions in [Goh03,CM05], but to explain these we’ll need to define the model more precisely

  12. SSE Algorithms • Keygen(1k): outputs symmetric key K • BuildIndex(K, {D1, ..., Dn}): outputs secure index I • Trapdoor(K, w): outputs a trapdoor Tw • Search(I, Tw): outputs identifiers of documents containing w (id1, ..., idm)

  13. INDEX keyword SSE System Operation • Secure index: additional data structure that helps the server to search(following [Goh03] terminology) • Symmetricallyencrypted data: client performs encryption himself • Trapdoors: associate a trapdoor to keywords which enables server to search while keeping keyword hidden keyword

  14. Our model • History: documents and keywords • View: encrypted documents, index, trapdoors • Trace: length of documents, search outcomes, search pattern

  15. Our Intuition • Previous intuition • “A secure SSE scheme should not leak anything beyond the outcome and the pattern of a search” • A more “formal intuition” • “any function about the documents andthe keywords that can be computed from the encrypted documents, the index andthe trapdoors can be computed from the length of the documents, the search outcomes andthe search pattern”

  16. Issues with Goh’s SSE security definition • IND2-CKA: indistinguishability against chosen-keyword attacks • “any function of the documents that can be computed from the encrypted documents andthe index can be computed from the length of the documents andthe search outcomes” • Issue: says nothing about keywords or trapdoors • Important Note: [Goh03] considers more than SSE and notes that secure trapdoors is not necessary for all the applications considered. Also Z-IDX has secure trapdoors. • Why not prove index secure in the sense of IND2-CKA and trapdoors “secure” using another definition? • We show that there exists an SSE scheme that has • IND2-CKA indexes and trapdoors that are “secure” • but when taken together, adversary can recover keyword

  17. Issues with CM’s SSE security definition • “CM security” • “any function that can be computed about the documents and keywords given the ciphertexts, the index andthe trapdoors can be computed from the length of the documents andthe search outcomes” • Issues • leaves out search pattern (proofs assume unique queries) • order of quantifiers implies that there will always exist a simulator that can evaluate function on documents and keywords • Only guarantees security against non-adaptive adversaries

  18. What is adaptiveness? • Non-adaptive adversaries make search queries without seeing the outcome of previous searches • Adaptive adversaries can make search queries as a function of the outcome of previous searches • What are the implications of adaptiveness?

  19. SI w1 SI w2 w1 w2 w3 w4 w3 Modeling adaptiveness Non-Adaptive [SWP00,Goh03,CM05,...] Adaptive (new)

  20. Outline • Motivation • Overview of privacy-preserving searching • Searchable symmetric encryption • Revisiting security definitions for SSE • “Non-adaptive” definitions and construction • “Adaptive” definitions and construction • Extensions

  21. Non-adaptive security • “any function about the history thatcan be computed from the view can be computed from the trace” • history: documents and keywords • view: encrypted documents, index, trapdoors, • trace: document lengths, search outcomes, searchpattern

  22. Austin Baltimore Washington SSE-1 • Building a Secure Index

  23. SSE-1 • Building a Secure Index Austin Baltimore Washington

  24. P(Austin) P(Baltimore) P(Washington) SSE-1 • Building a Secure Index • P: PRP • F: PRF F(Austin) = KA Austin F(Baltimore) = KB Baltimore F(Washington) = KW Washington

  25. Trapdoor := (addr, key) D8, D10 SSE-1 • Searching addr := P(Baltimore) key := F(Baltimore) Baltimore

  26. Technical issues • We overlooked many technical details • padding and shuffling • Efficient storage of sparse tables • large address space; small number of entries • FKS dictionaries [Fredman-Komlos-Szemeredi84] • storage: O(#entries) • lookup: O(1)

  27. Outline • Motivation • Overview of privacy-preserving computation • Searchable symmetric encryption • Revisiting security definitions for SSE • “Non-adaptive” definitions and construction • “Adaptive” definitions and construction • Extensions

  28. Adaptive security • “any function about the partial history thatcan be computed from the partial view can be computed from the partial trace” • partial history: documents and keywords • partial view: encrypted documents, index, trapdoors, • partial trace: document lengths, search outcomes, search pattern

  29. Adaptive security • Do we need revised SSE constructions? • Are previous constructions adaptively secure? • Technicalchallenge: simulator must be able to “fake” trapdoors after having committed to index • Previous constructions do not have this property • Unfortunately, this is expensive!

  30. SSE-2 • Similar to SSE-1 • Pre-processing and padding • simulator can commit to an index before query is issued • and still build valid trapdoors after query is issued • Constant blowup in • size of trapdoors • size of index • server search time

  31. Comparison • n: total # of documents d: # of documents that contain word

  32. Outline • Motivation • Overview of privacy-preserving searching • Searchable symmetric encryption • Revisiting security definitions for SSE • “Non-adaptive” definitions and construction • “Adaptive” definitions and construction • Extensions

  33. Multi-User SSE

  34. Multi-User SSE • Indexes and trapdoors require same security notions as single-user SSE • Revocation: owner can revoke searching privileges • robust against user collusions • Anonymity: server should not know who initiated search • Simple construction that transforms single-user SSE schemes to multi-user SSE schemes • broadcast encryption (revocation) • PRPs

  35. Open Questions • Constant-round schemes that hide everything, even the access pattern • Constant-round Searching for Boolean combinations of keywords (note that with logarithmic rounds already follows from [Ost,GO].) • Conjunctive searchable encryption [GSW04, PKL04, BW06] • Disjunctive ?

  36. Conclusions • Weakening “complete security” is delicate • point out issues with previous attempts • Introduce new definitions • non-adaptive: simulation and indistinguishability-based • adaptive: simulation and indistinguishability-based • Efficient and practical constructions • Multi-user setting

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