Privacy and Identity Management in Cloud

1
Privacy and Identity Management in Cloud
Rohit Ranchal, Bharat Bhargava, Pelin Angin,
Noopur Singh, Lotfi Ben Othmane, Leszek
Lilien Department of Computer Science Purdue
University, Western Michigan University
rranchal, bbshail_at_purdue.edu,
leszek.lilien_at_wmich.edu Mark Linderman mark.linde
rman_at_rl.af.mil Air Force Research
Laboratory Rome, NY, USA This research was
supported by AFRL Rome, USA and NGC
2
Outline

• Motivation
• Identity Management (IDM)
• Goals of Proposed User-Centric IDM
• Mechanisms
• Description of proposed solution
• Advantages of the Proposed Scheme
• Conclusion Future Work
• References
• Questions?

3
Motivation
User on Amazon Cloud

• Name
• E-mail
• Password
• Billing Address
• Shipping Address
• Credit Card

• Name
• Billing Address
• Credit Card

• Name
• E-mail
• Password
• Billing Address
• Shipping Address
• Credit Card

• Name
• E-mail
• Shipping Address

• Name
• E-mail
• Shipping Address

4
Motivation
User on Amazon Cloud

• Name
• E-mail
• Password
• Billing Address
• Shipping Address
• Credit Card

• Name
• Billing Address
• Credit Card

• Name
• E-mail
• Password
• Billing Address
• Shipping Address
• Credit Card

• Name
• E-mail
• Shipping Address

• Name
• E-mail
• Shipping Address

5
Identity Management (IDM)

• IDM in traditional application-centric IDM model
• Each service keeps track of identifying
  information of its users.
• Existing IDM Systems
• Microsoft Windows CardSpace W. A. Alrodhan
• OpenID http//openid.net
• PRIME S. F. Hubner, Karlstad Univ
• These systems require a trusted third party and
  do not work on
• an untrusted host.
• If Trusted Third Party is compromised, all the
  identifying information
• of the users is also compromised leading to
  serious problems like
• Identity Theft.
• Latest ATT iPad leak

6
IDM in Cloud Computing

• Cloud introduces several issues for IDM
• Collusion between Cloud Services
• Users have multiple accounts associated with
  multiple service providers.
• Sharing sensitive identity information among
  services can lead to undesirable mapping of the
  identities to the user.
• Lack of trust
• Cloud hosts are untrusted
• Use of Trusted Third Party is not an option
• Loss of control
• Service-centric IDM Model
• IDM in Cloud needs to be user-centric

7
Goals of Proposed User-Centric IDM for the Cloud

1. Authenticate without disclosing identifying
   information
2. Ability to securely use a service while on an
   untrusted host (VM on the cloud)
3. Minimal disclosure and minimized risk of
   disclosure during communication between user and
   service provider (Man in the Middle,
   Side Channel and Correlation Attacks)
4. Independence from Trusted Third Party for
   identity information

8
Mechanisms in Proposed IDM

• Active Bundle L. Othmane, R. Ranchal
• Anonymous Identification A. Shamir
• Computing Predicates with encrypted data E. Shi
• Multi-Party Computing A. Shamir
• Selective Disclosure B. Laurie

9
Active Bundle

• Active bundle (AB)
• An encapsulating mechanism protecting data
  carried within it
• Includes data
• Includes metadata used for managing
  confidentiality
• Both privacy of data and privacy of the whole AB
• Includes Virtual Machine (VM)
• performing a set of operations
• protecting its confidentiality
• Active BundlesOperations
• Self-Integrity check
• E.g., Uses a hash function
• Evaporation/ Filtering
• Self-destroys (a part of) ABs sensitive data
  when threatened with a disclosure
• Apoptosis
• Self-destructs ABs completely

10
Active Bundle Scheme

• Metadata
• Access control policies
• Data integrity checks
• Dissemination policies
• Life duration
• ID of a trust server
• ID of a security server
• App-dependent information

• E(Name)
• E(E-mail)
• E(Password)
• E(Shipping Address)
• E(Billing Address)
• E(Credit Card)

• Sensitive Data
• Identity Information
• ...

• Virtual Machine (algorithm)
• Interprets metadata
• Checks active bundle integrity
• Enforces access and dissemination control
  policies

E( ) - Encrypted Information
11
Anonymous Identification

• Use of Zero-knowledge proofing for user
  authentication without disclosing its identifier.

User on Amazon Cloud
ZKP Interactive Protocol
User Request for service
Function f and number k

1. E-mail
2. Password

fk(E-mail, Password) R

1. E-mail
2. Password

Authenticated
12
Interaction using Active Bundle
AB information disclosure
Active Bundle Destination
User Application
Active Bundle
Active Bundle (AB)
Active Bundle Creator
Audit Services Agent (ASA)
Security Services Agent (SSA)
Directory Facilitator
Trust Evaluation Agent (TEA)
Active Bundle Coordinator
Active Bundle Services
13
Predicate over Encrypted Data

• Verification without disclosing unencrypted
  identity data.

Predicate Request

• E-mail
• Password
• E(Name)
• E(Shipping Address)
• E(Billing Address)
• E(Credit Card)

• E(Name)
• E(Billing Address)
• E(Credit Card)

Age Verification Request Credit Card
Verification Request
14
Multi-Party Computing

• To become independent of a trusted third party
• Multiple Services hold shares of the secret key
• Minimize the risk

Predicate Request

• E(Name)
• E(Billing Address)
• E(Credit Card)

K1
K2
K3
Kn
Key Management Services
Decryption of information is handled by the Key
Management services
15
Multi-Party Computing

• To become independent of a trusted third party
• Multiple Services hold shares of the secret key
• Minimize the risk

Predicate Reply

• Name
• Billing Address
• Credit Card

K1
K2
K3
Kn
Key Management Services
Age Verified Credit Card Verified
16
Selective Disclosure

• User Policies in the Active Bundle dictate
  dissemination

Selective disclosure

• E-mail
• Password
• E(Name)
• E(Shipping Address)
• E(Billing Address)
• E(Credit Card)

• E-mail
• E(Name)
• E(Shipping Address)

e-bay shares the encrypted information based on
the user policy
17
Selective Disclosure
Selective disclosure

• E-mail
• E(Name)
• E(Shipping Address)

• E(Name)
• E(Shipping Address)

e-bay seller shares the encrypted information
based on the user policy
18
Selective Disclosure
Selective disclosure

• E-mail
• E(Name)
• E(Shipping Address)

• Name
• Shipping Address

• Decryption handled by Multi-Party Computing as in
  the previous slides

19
Selective Disclosure
Selective disclosure

• E-mail
• E(Name)
• E(Shipping Address)

• Name
• Shipping Address

• Fed-Ex can now send the package to the user

20
Identity revealed in the Cloud
User on Amazon Cloud

• E-mail
• Password

• Name
• Billing Address
• Credit Card

• Name
• E-mail
• Password
• Billing Address
• Shipping Address
• Credit Card

• E-mail

• Name
• Shipping Address

21
Characteristics and Advantages

• Ability to use Identity data on untrusted hosts
• Self Integrity Check
  
• Integrity compromised- apoptosis or evaporation
  
• Data should not be on this host
• Establishes the trust of users in IDM
• Through putting the user in control of who has
  his data and how is is used
• Identity is being used in the process of
  authentication, negotiation, and data exchange.
• Independent of Third Party for Identity
  Information
• Minimizes correlation attacks
• Minimal disclosure to the SP
• SP receives only necessary information.

22
Conclusion Future Work

• Problems with IDM in Cloud Computing
• Collusion of Identity Information
• Prohibited Untrusted Hosts
• Usage of Trusted Third Party
• Proposed Approaches
• IDM based on Anonymous Identification
• IDM based on Predicate over Encrypted data
• IDM based on Multi-Party Computing
• Future work
• Develop the prototype, conduct experiments and
  evaluate the approach

23
References

• 1 C. Sample and D. Kelley. Cloud Computing
  Security Routing and DNS Threats,
  http//www.securitycurve.com/wordpress/, June
  23,2009.
• 2 W. A. Alrodhan and C. J. Mitchell. Improving
  the Security of CardSpace, EURASIP Journal on
  Information Security Vol. 2009,
  doi10.1155/2009/167216, 2009.
• 3 OPENID, http//openid.net/, 2010.
• 4 S. F. Hubner. HCI work in PRIME,
  https//www.prime-project.eu/, 2008.
• 5 A. Gopalakrishnan, Cloud Computing Identity
  Management, SETLabsBriefings, Vol7,
  http//www.infosys.com/research/, 2009.
• 6 A. Barth, A. Datta, J. Mitchell  and H.
  Nissenbaum. Privacy and Contextual
  Integrity Framework and Applications, Proc. of
  the 2006 IEEE Symposium on Security and Privacy,
  184-198.
• 7 L. Othmane, Active Bundles for Protecting
  Confidentiality of Sensitive Data throughout
  Their Lifecycle, PhD Thesis, Western Michigan
  Univ, 2010.
• 8 A. Fiat and A. Shamir, How to prove yourself
  Practical Solutions to Identification and
  Signature Problems, CRYPTO, 1986.
• 9 A. Shamir, How to Share a Secret,
  Communications of the ACM, 1979.
• 10 M. Ben-Or, S. Goldwasser and A. Wigderson,
  Completeness theorems for non-cryptographic
  fault-tolerant distributed computation, ACM
  Symposium on Theory of Computing, 1988.
• 11 E. Shi, Evaluating Predicates over
  Encrypted Data, PhD Thesis, CMU, 2008.

24

• Thank you!
• Any question?

25
Approach - 1

• IDM Wallet
• Use of AB scheme to protect PII from untrusted
  hosts.
• Anonymous Identification
• Use of Zero-knowledge proofing for authentication
  of an entity without disclosing its identifier.

26
Components of Active Bundle (Approach 1)

• Identity data Data used during authentication,
  getting service, using service (i.e. SSN, Date of
  Birth).
• Disclosure policy A set of rules for choosing
  Identity data from a set of identities in IDM
  Wallet.
• Disclosure history Used for logging and auditing
  purposes.
• Negotiation policy This is Anonymous
  Identification, based on the Zero Knowledge
  Proofing.
• Virtual Machine Code for protecting data on
  untrusted hosts. It enforces the disclosure
  policies.

27
Anonymous Identification (Approach 1)

• Anonymous Identification
• (Shamir's approach for Credit Cards)
• IdP provides Encrypted Identity Information to
  the user and SP.
• SP and User interact
• Both run IdP's public function on the certain
  bits of the Encrypted data.
• Both exchange results and agree if it matches.

28
Usage Scenario (Approach 1)
29
Approach - 2

• Active Bundle scheme to protect PII from
  untrusted hosts
• Predicates over encrypted data to authenticate
  without disclosing unencrypted identity data.
• Multi-party computing to be independent of a
  trusted third party

30
Usage Scenario (Approach 2)

• Owner O encrypts Identity Data(PII) using
  algorithm Encrypt and Os public key PK. Encrypt
  outputs CTthe encrypted PII.
• SP transforms his request for PII to a predicate
  represented by function p.
• SP sends shares of p to the n parties who hold
  the shares of MSK.
• n parties execute together KeyGen using PK, MSK,
  and p, and return TKp to SP.
• SP calls the algorithm Query that takes as input
  PK, CT, TKp and produces p(PII) which is the
  evaluation of the predicate.
• The owner O is allowed to use the service only
  when the predicate evaluates to true.

31
Representation of identity information for
negotiation

• Token/Pseudonym
• Identity Information in clear plain text
• Active Bundle

32
Motivation Authentication Process using PII

• Problem Which information to disclose and how
  to disclose it.