Fuzzy Keyword Search overEncrypted Data inCloud Computing

Jin Li, Qian Wang, Cong Wang,Ning Cao, Kui Ren, and Wenjing Lou

IEEE 29th International Conference on Computer CommunicationsINFOCOM 2010

San Diego, CA - USA - 2010

Presentation by Mateus Cruz

Introduction Preliminaries Proposal Conclusion

OUTLINE

1 Introduction

2 Preliminaries

3 Proposal

4 Conclusion

Introduction Preliminaries Proposal Conclusion

OUTLINE

1 Introduction

2 Preliminaries

3 Proposal

4 Conclusion

Introduction Preliminaries Proposal Conclusion

SCENARIO

Outsourcing dataPrivacy concernsEncryption as a solutionSearch encrypted data

I Only considers exact matching

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PROPOSAL

Fuzzy keyword search over encrypted dataUse of edit distanceEfficient construction of fuzzy sets

I Smaller sets

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RELATED WORK

Plaintext fuzzy keyword searchI Dictionary and statistical attacks

Searchable encryptionI Only supports exact search

Secure multiparty computationI High complexity and slow execution

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Introduction Preliminaries Proposal Conclusion

OUTLINE

1 Introduction

2 Preliminaries

3 Proposal

4 Conclusion

Introduction Preliminaries Proposal Conclusion

ARCHITECTURE

RolesI Data owner, data users and cloud server

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SYSTEM MODEL

Collection of N encrypted filesI C = {F1,F2, ...,FN}

Predefined set of p distinct keywordsI W = {w1,w2, ...,wp}

Each file is indexed by an IDI And it is linked to a set of keywords

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THREAT MODEL

Semi-trusted serverNothing should be leaked

I Except the result and search patterns

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EDIT DISTANCE

Number of operations to transform onestring into another

I SubstitutionI DeletionI Insertion

Sw ,dI Set of words that satisfy ed(w ,w ′) ≤ d

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FUZZY KEYWORD SEARCH

InputI Encrypted files C = (F1,F2, ...,FN)I Set of distinct keywords W = {w1,w2, ...,wp}I Query (w , k) (edit distance threshold k )

OutputI If w = wi ∈W , return FIDwI If w /∈W , return {FIDwi}

– ed(w ,wi) ≤ k

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Introduction Preliminaries Proposal Conclusion

OUTLINE

1 Introduction

2 Preliminaries

3 Proposal

4 Conclusion

Introduction Preliminaries Proposal Conclusion

PROPOSED APPROACHES

Straightforward approachWildcard-based approach

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STRAIGHTFORWARD APPROACH

Symmetric encryption schemeI Setup(λ)

– Receives security parameter λ– Outputs a secret key sk

I Enc(sk , ·)I Dec(sk , ·)

Tw is a trapdoor of keyword wI Twi = f(sk ,wi)

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FUZZY SETS CONSTRUCTION

Swi ,d for each wi ∈W (1 ≤ i ≤ p)I Edit distance d

Straightforward constructionI Enumerate all possible words w ′

i such thated(wi ,w ′

i ) ≤ d

Examplewi = CASTLEPossibilities for one substitution:{AASTLE , . . . ,ZASTLE}Still have to consider deletion and insertion!

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INDEX CONSTRUCTION

Computation of trapdoorsI Tw ′

i= f foreachw ′

i ∈ Swi ,d

Encryption of FIDwiI Set of file IDs whose files contain wiI Enc(sk ,FIDwi ||wi)

Creates and uploads index tableI {({Tw ′

i}w ′

i ∈Swi ,d,Enc(sk ,FIDwi ||wi))}wi∈W

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FUZZY SEARCH

An authorized user...I Computes TwI Sends Tw to the server

The server...I Look for the trapdoor in the index tableI Returns {Enc(sk ,FIDwi ||wi)}

The user...I Decrypts the resultsI Retrieve relevant files

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PROBLEMS

Large fuzzy setsHigh storage costThree edit operations

I Substitution, deletion, insertion

Demand for smaller fuzzy sets

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WILDCARD-BASED APPROACHTry to generate smaller fuzzy setsWildcards

I Denote operations at the same positionWildcard-based fuzzy set

I Swi ,d = {S′wi ,0,S

′wi ,1, . . . ,S

′wi ,d}

I S′wi , τ is the set of words w ′i with τ wildcards

Examplew = CASTLE , τ = 1SCASTLE ,1 = {CASTLE , ∗CASTLE , ∗ASTLE ,

C ∗ ASTLE ,C ∗ STLE , . . . ,CASTL ∗ E ,CAST ∗ E ,CASTLE∗}

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EFFICIENT FUZZY KEYWORD SEARCH

The data owner...I Constructs fuzzy keyword set Swi ,d

– Using the wildcard-based techniqueI Computes trapdoor set {T ′

wi}

– For each w ′i ∈ Swi ,d

I Encrypts FIDwi as Enc(sk ,FIDwi ||wi)

An authorized user...I Computes the trapdoor set {Tw ′}w ′∈Sw,k

The server...I Receives the trapdoor set {Tw ′}w ′∈Sw,kI Returns all possible identifiers{Enc(sk ,FIDwi ||wi)}

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ANALYSIS

Keyword wi with length `Straightforward approach

I Size of Swi ,1 will be (2`+ 1)× 26 + 1Wildcard-based approach

I Size of Swi ,1 will be 2`+ 1 + 1Reduced storage requirements

I O(`d)

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Introduction Preliminaries Proposal Conclusion

OUTLINE

1 Introduction

2 Preliminaries

3 Proposal

4 Conclusion

Introduction Preliminaries Proposal Conclusion

SUMMARY

Wildcard-based approachI A wildcard denotes all operations

Efficient construction of fuzzy setsI Reduced storage requirements

Secure regarding search privacy

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