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Security and Privacy in Cloud Computing

Security and Privacy in Cloud Computing. Ragib Hasan Johns Hopkins University en.600.412 Spring 2010. Lecture 7 03/ 28/2011. Provenance. http://moma.org/collection/provenance/items/644.67.html. L'artiste et son modèle (1928), at Museum of Modern Art.

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Security and Privacy in Cloud Computing

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  1. Security and Privacy in Cloud Computing Ragib HasanJohns Hopkins Universityen.600.412 Spring 2010 Lecture 7 03/28/2011

  2. Provenance http://moma.org/collection/provenance/items/644.67.html L'artiste et son modèle (1928), at Museum of Modern Art • Provenance: from Latin provenire ‘come from’, defined as • “(i) the fact of coming from some particular source or quarter; origin, derivation. • (ii) the history or pedigree of a work of art, manuscript, rare book, etc.; a record of the ultimate derivation and passage of an item through its various owners” (Oxford English Dictionary) • In other words,Who owned it, what was done to it, how was it transferred … • Widely used in arts, archives, and archeology, called the Fundamental Principle of Archival en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

  3. Data Provenance en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan • Definition* • Description of the origins of data and the process by which it arrived at the database. [Buneman et al.] • Information describing materials and transformations applied to derive the data. [Lanter] • Metadata recording the process of experiment workflows, annotations, and notes about experiments. [Greenwood] • Information that helps determine the derivation history of a data product, starting from its original sources. [Simmhan et al.] *Simmhan et al. A Survey of Provenance in E-Science. SIGMOD Record, 2005.

  4. Forensics and Provenance in Clouds • Cloud provenance can be • Data provenance: Who created, modified, deleted data stored in a cloud (external entities change data) • Process provenance: What happened to data once it was inside the cloud (internal entities change data) • Cloud provenance should give a record of who accessed the data at different times • Auditors should be able to trace an entry (and associated modification) back to the creator en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

  5. Privacy questions Should the cloud provider know the identity of cloud users? Should cloud users know the identity of other users in the same group? en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

  6. The “Bread and Butter” paper Lu et al., Secure Provenance: The Essential Bread and Butter of Data Forensics in Cloud Computing, AsiaCCS 2010 Problem • To preserve user privacy and allow anonymous authentication/access in a cloud • To determine authorship of data, i.e., to bind data versions to user identities in a cloud en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

  7. Threat Model • Who are the key players? • Users • SM • SP • Who trusts who? • Users: trust the SM, but not the SP • SP: Trust SM • SM: ? • What attacks can happen? en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

  8. System Model SM: Manages the whole system(?), registers cloud users and providers, issues keys SP: Cloud service provider, manages access to cloud resources Users: A user is part of a group of authorized principals who can access group resources en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

  9. Secure provenance (according to the paper) By secure provenance, the authors imply • Users can anonymously authenticate themselves as part of authorized users/groups to the cloud provider • Users can anonymously access and modify resources • Encrypted data stored by a user can be decrypted by other users from the same group • If necessary, the SM can trace a data item to the user who created it en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

  10. Setup Master Key K Param (Public Parameters) SM Inputs: Security parameter k Output: Master key, public parameters en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

  11. User/provider registration Master Key User identity Ui Private key ski Param (Public Parameters) Tracking list Inputs: Master key, public parameters, user identity Outputs: Private key, entry in tracking list en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

  12. User-cloud interaction (1) χ σA = signski(Yi||χ) σP / aski User anonymously authenticate herself to the cloud Cloud provider can check that the signature was made with a key issued by the SM en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

  13. User-cloud interaction (2) EncryptedData: C = encrypt(M) Sig = signaski(C) Store C and σA Provider stores Signatures and authentication information during each access en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

  14. Identifying authorship σA User identity en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

  15. Confidentiality preservation Each user gets a different authorized group user access key Any group user access key can be used to decrypt a ciphertext created by other users in the same group en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

  16. Discussion Suppose Amazon S3 implements such a model. What will be the advantages, and what will be the disadvantages? en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

  17. What about other provenance in computation clouds? If the data is being manipulated by processes running in the cloud, how will the problem change? en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

  18. Further Reading Ragib Hasan, Radu Sion, and Marianne Winslett, Protecting History Forgery with Secure Provenance, ACM Transactions on Storage, December 2009 en.600.412 Spring 2011 Lecture 7 | JHU | Ragib Hasan

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