secure search in cloud computing - central south...

Secure Search in Cloud Computing

2016 Central South University Workshop on Trusted ComputingJune 7- June 8, 2016

Presenter: Dr. Qin LiuAffiliation: Hunan University

Email:gracelq628@hnu.edu.cn

1

2

3

4

Secure Search

Public key setting

Future Work

Symmetric key setting

1

Searchable Encryption

Access pattern: which files have been returnedSearch pattern: whether two searches were performed for the same keyword

Symmetric key setting: the keys encrypting the index and the token are the same. Asymmetric key setting: the keys encrypting the index and the token are the different.

How to preserve user privacy during search?

2 Public Key Setting

• Bob sends to Alice an email encrypted under Alice’s public key.

• Alice’s email gateway wants to test whether the email contains the keyword urgent so that it could route the email to her PDA immediately.

• But,Alice does not want the email gateway to be able to decrypther messages

Boneh, Dan, et al. "Public key encryption with keyword search." Advances in Cryptology-Eurocrypt 2004. Springer Berlin Heidelberg, 2004.

Efficient Searchable Encryption

• Problem• The user needs to perform decryption• Thin client has only limited resources

• Requirements• Enable the cloud to perform partial decryption without compromising search privacy• User can access data from the cloud anytime and anywhere with any devices

Liu Q, Wang G, Wu J. An efficient privacy preserving keyword search scheme in cloud computing[C]//Computational Science and Engineering, 2009. CSE'09. International Conference on. IEEE, 2009, 2: 715-720.

2 Public Key Setting

Efficient Searchable Encryption

• Key technique• Alice takes both Bob and CSP’s public key as inputs of the

encryption algorithm• CSP uses its secret key to perform partial decrypt and generate

an intermediate value• Bob use the intermediate value to quickly recover data

2 Public Key Setting

Private Search (PS)

Cloud

Bob

[1] [1] [0] [0]

F1 F2 0 NA

A compressed version of all files

F1: {A,B}

F2:{B,D}

F3:{C,D}

Given a public dictionary that contains all keywords, e.g.,

dictionary=<A,B,C,D>.

Bob wants to retrieve files with keywords A and B

2 Public Key Setting

R. Ostrovsky and W. Skeith III, “Private searching on streaming data,”in Proceedings of CRYPTO, 2005.

Private Search (PS)

Homomorphic encryption

E(x)*E(y) = E(x+y)

E(x)^y = E(x*y)

F1: { A, B} F2: {B,D} F3: {C,D}

F1 F2 0 NA

[1] [1] [0] [0]key trick: map unmatched files to 0

F1 NA

F1 F2 F3

F2 0

survival collision survival unmatched

E(F2)* E(0) =E(F2)

2 Public Key Setting

Liu Q, Tan C C, Wu J, et al. Cooperative private searching in clouds[J]. Journal of Parallel and Distributed Computing, 2012, 72(8): 1019-1031.

Problem for simple PS• Processing each query is expensive. Given n users, the cloud

needs to execute n queries• Performance bottleneck on the cloud

• COPS Architecture• A proxy server (ADL) is introduced between the users and the

cloud (trusted)• Aggregate user queries

• Distribute searching results

2 Public Key Setting

Cooperative Private Search (COPS)

Cooperative Private Search (COPS) Key technique

• The user and the cloud share• Shuffle functions shuffle the dictionary and the query

• --- to preserve search privacy

• Pseudonym function: hide file name

• Obfuscated function: hide file content

• ---preserve access privacy

Key merits• User privacy is preserved from

• The cloud

• The proxy server

• Other users

2 Public Key Setting

Efficient Information Retrieval for Ranked Queries (EIRQ) Problem for Simple COPS

• No ranked queries• The cloud returns all matched files

2 Public Key Setting

G. Wang, Q. Liu, F. Li, S. Yang, and J. Wu,"Outsourcing Privacy-Preserving Social Networks to a Cloud," Proc. Of 32nd IEEE International Conference on Computer Communications(IEEE INFOCOM 2013)Q. Liu, C. C. Tan, J. Wu, and G. Wang, “Towards Differential Query Services in Cost-Efficient Clouds,” IEEE Transactions on Parallel and Distributed Systems (TPDS), 2014

Queries are classified into 0,1,…,r-1 ranks.

Rank-i query retrieves (1-i/r) percentage of matched files

Files that match rank 0 queries

Files that match rank 1 queries

Files that match rank i queries

Will not be filtered Filtered with probability 1/r

Filtered with probability i/r

……… …

The cloud

Cannot know which files are filtered/returned

Cannot know each queries’ rank

Efficient Information Retrieval for Ranked Queries (EIRQ)

2 Public Key Setting

Key techniques: Construct a mask matrix to protect query ranks

Filter files without knowing which files are filtered

QueryGenStep 1:

User ADL Cloud

Keywords, rank

FileFilter

FileRecovery

MatrixConstruct

Step 2:

Step 4:

Step 3:

Mask matrix

Buffer

Certain percentage of files matching user keywords

Efficient Information Retrieval for Ranked Queries (EIRQ)

2 Public Key Setting

ADL constructs a mask matrix that is encrypted with its publics key, and sends it to the cloud

Cloud

ADL

A

B

C

D

[1] [1]

[1] [1]

[1] [0]

[0] [0]

… …

[0] [0]

{A, B} Rank 0

{A, C} Rank 1

Alice

Bob

Number of ranks, r=2

Number of keywords

Construct Mask Matrix

Efficient Information Retrieval for Ranked Queries (EIRQ)

2 Public Key Setting

Cloud

F1: { A, B} F2: {B, D} F3: {C, D}

buffer

ADL

…

A

B

C

D

[1] [1]

[1] [1]

[1] [0]

[0] [0]

… …

[0] [0]

The cloud chooses a random column for each file

…

F1 and F2 will be returnedF3 will be filtered with 50%

A file, matched rank i query,

the probability to be filtered i/r

For F3: 50% 50%

E(0)*E(0)=E(0) E(0)*E(0)=E(0)

E(0)^F3 =E(0) E(1)^ F3 =E(F3)

Filter Files

Efficient and Privacy-Preserving Search in Multi-Source Personal Health Record Clouds

Xin Yao, Yaping Lin, Qin Liu, Shuai Long, “Efficient and Privacy-Preserving Search in Multi-Source Personal Health Record Clouds”, accepted by ISCC 2015.

2 Symmetric Key Setting

ICA3PP 2015

（Xiaoyu Zhu, GuoJun Wang, and Qin Liu）

Verifiable Dynamic Fuzzy Search over Encrypted Data in Cloud Computing

•The scheme can not only fulfill the fuzzy search functionality while maintaining

privacy, but also can update documents dynamically and support the verifiability

of the searching result.

What are we doing？

• Dynamic Attribute-based Keyword Search

in Cloud Computing (submitted to MASS 2016)

• Verifiable Ranked Search over Dynamic Encrypted

Data in Cloud Computing (Submitted to ICNP 2016)

• Verifiable Dynamic Search over Encrypted Data in Untrusted Cloud (Prepared for ICA3PP 2016)

• Efficient Multi-keyword Fuzzy Search in Cloud Computing (Prepared for Infocom 2017)

4 Future Work

Verifiable Searchable Encryption

Fuzzy keyword search

Multi-keyword search

Thank You !