The Security of DAS—Auditing for Outsourced Data

Only concern with Simple Selection Query The Process: [ Server has stored the fake tuples, which user knows clearly.] 1. The User send a query Q to the Server 2. Server execute Q on its site & return result R to User 3. User check on its site whether all checking tuples that Covered By Q are really all in result Q
h(1)
h(2)
h(3) h(4)
Signature(h(1|2|3|4))
h(1) h(2)
Signature(h(1|2|3|4))
Select h(1), h(3|4), Signature(h(1|2|3|4) } •A=2, {A from T where A <3 •A={1,2}, { h(3), h(4), Signature(h(1|2|3|4) }
•Drawback: 1. Have to store the set of checking tuples at the client site, which may cause great storage overhead 2. Search may inefficient.
[Min Xie 2007 VLDB] Freshness [Min Xie 2008 EDBT] [Haixun Wang 2008 CIKM]

Fake Tuple Method


Dual Encryption Method

Challenge Token Method

Motivation：to prevent laziness
Outline

Background Current Methods

Signature Based Data Structure Based
Probability Based

My thinking
Current methods

Challenge Token Method

[Sion 2005 VLDB]
•Merkle Hash Tree Based Method
Server
etuple
t1=(10,1) x4Z3tfX2ShOSM t2=(20,2) JpO8eLTVgwV1E
a
10 20
b
E(1)=2 E(2)=5
Data Structure Based
•Merkle Hash Tree Based Method


There is a probability that the attacker can escape from being caught.
Correctness Concern

Goal: Protect Tuple From Being Tampered Assume the data has n fields {A1, A2, …, An} A tuple t (a1, a2, …, an)
Client S1
H(qi(S1)) {q1,q2,…,qn } {r1,r2,…,rn } i
Server S1
H is a One- Way HashingFunction
Current methods

Integrity Auditing of Outsourced Data

Challenge Token Method [Sion 2005 VLDB] Fake Tuple Method [Min Xie 2007 VLDB] Freshness [Min Xie 2008 EDBT] Dual Encryption Method [Haixun Wang 2008 CIKM]

My thinking
Introduction

Providing Database As-a-Service Server-Tamper management task in house, Instead of taking care of all the databasewith data all the user’s data is sent a service provider data stored in server to Insert, delete or alter The BENEFIT To be lazy User can eliminate in-house hardware, software and expertise needs Hostile Deleting to run DBMS



Fake Tuple Method
Outline

Motivation Security Model & Checking Method


Checking Tuple Generating
Freshness Guarantee
Drawbacks of previous methods
The Security of DAS— Auditing for Outsourced Data
闫巧芝 2009.4.16
Outline

Background
Current approach

Signature Based Data Structure Based Probability Based ★

Major Concerned Factor:

The Server-Side is not a purely traditional relational engine, need to combine with some additional data structure
How about Server just a traditional Relation Engine ? How to check Correctness ? How to check Completeness ?

•Validation of query results (Correct & Complete & Freshness)
Outline

Introduction
Current apprData Structure Based Probability Based

H (a0 a1 ... an ) Original Tuple header H (a0 a1 ... an ) 1 Checking Tuple
H is a One- Way HashingFunction
Checking Method
TO

Goal of our checking Checking Tuples Covered by Q should contained in the result
Query Q
Service Provider
Table T
A 1 2 h(1|2) h(1|2|3|4)
User Device
Public Key
SELECT A FROM T WHERE A = 2
Merkle Tree
h(3|4)
T’
A 2 h(1|2)
VO
h(1|2|3|4) h(3|4)
3 4

A Naï Solution ve We randomly generate a series of checking tuples Maintain a copy at the client site When a query Q is send to the server, also run the query on the client site, check whether the checking tuple count of the client site result equals count in the result from server
Data Structure Based

Merkle Hash Tree Based Method
优点 缺点
◇ 不支持join sum、avg的正确性/完整性的验证
☆ 可以验证元组正确性 ☆ 能验证简单的元组级的range query的结果完整性
◇ 每个涉及范围查询的属性都需建立MHT消耗大
◇ 满二叉树，数据的每次更新都需调整MHT，维护困难 ◇ 结点多，传输代价大。
•Starting point： •Client audit the result to guarantee the server’s honesty

My thinking
Signature Based
基于数组签名验证方法 优点--缺点 逐条验证，加密解密时间开销较大; 结果集大时，所耗带宽与验证时间很大; 批处理验证提高效率; 将多个数据签名集成为一个; 返回的结果集只有一个签名; 减少带宽消耗和客户端的计算; 只能对同一个用户的签名进行集成; 可以将多个用户的签名统一集成;。 对多用户签名的情况，验证的开销很大; 可验证range query的完整性; 需防止元组顺序信息的泄漏; 验证结果集正确性的消耗大;
可验证正确性和Range Query的完整性
参考杨平平报告内容