Transcript Privacy *Preserving Public Auditing for Data Security in
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
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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 paper
Some 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 paper
The 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 Initilization Motivation: 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 Initilization • • • Nonmenclature Explanation(2) Public key: ( 封裝 ) keys for locking a box Private key: ( 開箱 ) keys for unlocking a box MAC: ( content 檢查碼 ) message authentication code.
Each piece of data has a MAC code, derived from its • • 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 Initilization • • • Phase Nonmenclature: User KeyGen: generate the key SigGen: gengerate the verification of meta data(MAC) CSP:Cloud Storage Provider GenProof: generate proof of data correctness TPA:Third Party Auditor VerifyProof:Audit proof from CSP(Amazon)
Have a little break...
Motivation and Initilization • Example 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 Initilization • Example 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 Initilization
Item
Number of keys Key is given to Mac is stored by … File is transferred to…
Example 1
1 鑑識官 Amazon Amazon and 鑑識官
Example 2
N 鑑識官 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
a
1 2
a
3
a
4 1 ( ) 1
f a
2 ( 2 ) 3 ( ) 3
f a
4 ( 4 Amazon回傳的Hash Code 2 ) ( 4 ) • • 關鍵在於： 單獨
f i
但是整體 1 ( ) 1
f a
2 ( 2 ) 3 ( ) 3
f a
4 ( 4 ) 1 ( ) 1
g a
2 ( 2 ) 3 ( ) 3
g a
4 ( 4 ) 正確對應關係，只有鑑識官知道(只有他有private key)
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 Auditing Mathematical Analysis
a a a a
1 2 3 ..
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a a a i
1
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3 ...
a i n
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
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Reference
Wikipedia: • Algebra: Michael Artin, 2 nd 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)