Privacy –Preserving Public Auditing for Data Security in

Cloud Computing

B97201006 林楷軒

Outline

• Overview of this paper

• Motivation and Initialization

• Detailed Mechanism

• Some Comments

• Reference

Overview of this paper

Overview of this paper• In one sentence,

Ensure your data authentication in cloud?

• Properties of cloud storage• Users always have availabe and scalable space

→Need not worry about running out of space• Users need not have real physical storage media

→Need not spend money on equipments

• Data is not near your hand →Data not accessible when network failure→How to make sure the data authentication?

Overview of this paperSome instances threatening your data in cloud

• Cloud Storage Provider deletes your data that you seldom access

• Cloud Storage Provider hides data loss incidnets

• Internal communication error in clusters of computers in Cloud(Amazon 2008,June 20)

Overview of this paperThe solution is:A third party checks you data authentication(Self-checking is too tiring)

Requirements:• Checks authentication while preserving privacy• [Exclusive]First model able to support scalable

and efficient auditing• [Exclusive]Security justified by concrete

experiments• [Mice.]No local copy of data, no more burden to

users

Motivation and Initialization

Motivation and InitilizationMotivation:Check the authentication of data

Nonmenclature Explanation(1):• TPA:Third Party Auditor• User:…• CSP:Cloud Storage Provider

鑑識官鄉民Amazon

Motivation and InitilizationNonmenclature Explanation(2)• Public key: (封裝 ) keys for locking a box• Private key: (開箱 ) keys for unlocking a box• MAC: (檢查碼 ) message authentication code.

Each piece of data has a MAC code, derived from its content

簡單舉例 (MD5)• MD5("The quick brown fox jumps over the lazy

dog")9e107d9d372bb6826bd81d3542a419d6

• MD5("The quick brown fox jumps over the lazy dog.")e4d909c290d0fb1ca068ffaddf22cbd0

Motivation and InitilizationPhase Nonmenclature:• User

KeyGen: generate the keySigGen: gengerate the verification of meta data(MAC)

• CSP:Cloud Storage ProviderGenProof: generate proof of data correctness

• TPA:Third Party AuditorVerifyProof:Audit proof from CSP(Amazon)

Have a little break...

Motivation and InitilizationExample One: Privacy Leaking• 鄉民 :– 生成一把鑰匙，丟給鑑識官– 製造 MAC ，丟給 Amazon– 上傳檔案給 Amazon– 鄉民刪除在自己硬碟上的檔案

• 檢查方式– 鑑識官向 Amazon 要檔案 ( 檔案外洩啦… )– 鑑識官自行生成 MAC ，檢查檔案

Motivation and InitilizationExample Two: Finitely many checking times• 鄉民 :

– 生成 N 把鑰匙，丟給鑑識官– 製造 N 種鑰匙的 MAC ，丟給鑑識官– 上傳檔案給 Amazon– 鄉民刪除在自己硬碟上的檔案

• 檢查方式– 鑑識官給 Amazon 鑰匙，並要求回傳對應 MAC 值– Amazon 回傳對應的 MAC 值給鑑識官– 鑑識官生成一次檢查碼，跟 Amazon 上的 MAC 做比

對

Motivation and InitilizationItem Example 1 Example 2

Number of keys 1 N

Key is given to 鑑識官 鑑識官Mac is stored by … Amazon 鑑識官File is transferred to… Amazon and 鑑識官 Amazon

優缺點分析：1. Example1鑑識官 :擁有鑰匙，所以可以無限次檢查檔案的完整與否Amazon:必須上傳檔案給鑑識官，暴露隱私，也增加工作量

2. Example2鑑識官保護了使用者隱私因為MAC是有限的，所以可以偽造答案

下一步，我們要分析：如先兼顧使用者隱私的同時，也讓鑑識官能無限次檢查檔案？

Detailed Mechanism(?)這份投影片，我採取的策略：以定性敘述，取代定量分析

Detailed Mechanism(?)Algebra:• Michael Artin• Algebra

Essential Parts: Group Theory

Link: Here

Detailed Mechanism(?)Cryptography:• Oded Goldreich• Foundations of Cryptography

Essential Parts: ???Link: Here

Detailed Mechanism(?)User Initilization• 鄉民 :

– 生成解密鑰匙，丟給鑑識官– 生成公開參數，丟給 Amazon– 生成驗證碼丟給 Amazon– 鄉民刪除在自己硬碟上的檔案

• 檢查方式– 鑑識官向 Amazon 要求檢查部分的檔案– Amazon 利用混合的公開參數，對原始檔案 Hash– Amazon 回傳 Hash 值、驗證碼– 鑑識官由解密鑰匙解密 Hash ，與驗證碼做比對

Detailed Mechanism(?)

我很難相信你聽得懂 = =

Detailed Mechanism(?)白話文解釋：• 抽樣檔案• 驗證碼 (stored in amazon)• Amazon 回傳的 Hash Code

關鍵在於：• 單獨 兩者的對應關係，沒有人清楚 ( 亂數生成 )• 但是整體

正確對應關係，只有鑑識官知道 ( 只有他有 private key)

1 2 3 4a a a a

1 1 2 2 3 3 4 4( ) ( ) ( ) ( )f a f a f a f a

1 1 2 2 3 3 4 4( ) ( ) ( ) ( )g a g a g a g a

i if g

1 1 2 2 3 3 4 4 1 1 2 2 3 3 4 4( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )f a f a f a f a g a g a g a g a

Detailed Mechanism(?)其他保證的性質：• Low Burden on Amazon:

Constant large sending block(mathematical analysis…)

• Theoretically, if amazon misses 1% data, TPA only needs to audit for 460, 300 samples with probability more than 99%, 95%

• Support for Batch AuditingMathematical Analysis 1 2 31 2 3.. ...

nn i i i ia a a a a a a a

Detailed Mechanism(?)Mathematical Analysis ：• Storage Correctness:

Amazon can not generate valid response toward TPA without faithfully storing the data

• Privacy Perserving Guarantee:TPA can not derive users’data conent from the information collected during the auditing porcess

Detailed Mechanism(?)Performance Analysis(Real Expriments)• Compared with old method(+Privacy)

• Batch Processing

Some Comments

Some Comments美中不足 ( 雞蛋裡挑骨頭 ?)• 過於理想化：

TPA 既不偏坦 CSP 也不偏袒使用者

• 對於動態資料未清楚說明：( 可以套用 [8] 的結果 )

• 只能偵測到問題，無法修復

• 99% 偵錯率夠嗎？

Reference

Reference• Wikipedia:

• Algebra:Michael Artin, 2nd Edition

• Foundations of Cryptography:Oded Goldreich

• Some slides from 陳君明老師

• Privacy Preserving Public Auditing for Data Storage Security in Cloud Computing(including some reference)

Q & A?