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Tamper-proof privacy auditing for artificial intelligence systems

Published: 13 July 2018 Publication History
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  • Abstract

    Privacy audit logs are used to capture the actions of participants in a data sharing environment in order for auditors to check compliance with privacy policies. However, collusion may occur between the auditors and participants to obfuscate actions that should be recorded in the audit logs. In this paper, we propose a Linked Data based method of utilizing blockchain technology to create tamperproof audit logs that provide proof of log manipulation and non-repudiation.

    References

    [1]
    Rafael Accorsi. Log data as digital evidence: What secure logging protocols have to offer? In Computer Software and Applications Conference, 2009. COMPSAC' 09. 33rd Annual IEEE International, volume 2, pages 398-403. IEEE, 2009.
    [2]
    Nicolai Anderson. Blockchain technology: A game-changer in accounting? Deloitte, March, 2016.
    [3]
    Denis Butin, Marcos Chicote, and Daniel Le Métayer. Log design for accountability. IEEE Security and Privacy Workshops, 2013.
    [4]
    Jeremy J Carroll, Christian Bizer, Pat Hayes, and Patrick Stickler. Named graphs. Web Semantics: Science, Services and Agents on the World Wide Web, 3(4):247-267, 2005.
    [5]
    Jordi Cucurull and Jordi Puiggalí. Distributed immutabilization of secure logs. In International Workshop on Security and Trust Management, pages 122-137. Springer, 2016.
    [6]
    Tom Heath and Christian Bizer. Linked data: Evolving the web into a global data space. Synthesis lectures on the semantic web: theory and technology, 1(1):1-136, 2011.
    [7]
    Andreas Kasten, Ansgar Scherp, and Peter Schauß. A framework for iterative signing of graph data on the web. In European Semantic Web Conference, pages 146-160. Springer, 2014.
    [8]
    Andreas Kasten. Secure semantic web data management: confidentiality, integrity, and compliant availability in open and distributed networks. PhD thesis, University of Koblenz and Landau, Germany, 2016.
    [9]
    Lory Kehoe, David Dalton, Cillian Leonwicz, and Thomas Jankovich. Blockchain disrupting the financial services industry? Deloitte, 2015.
    [10]
    Florian Kleedorfer, Yana Panchenko, Christina Maria Busch, and Christian Huemer. Verifiability and traceability in a linked data based messaging system. In Proceedings of the 12th International Conference on Semantic Systems, pages 97-100. ACM, 2016.
    [11]
    Sporny Manu. Building better blockchains. In Linked Data in Distributed Ledgers Workshop Keynote. WWW2017, 2017.
    [12]
    Ralph C Merkle. Protocols for public key cryptosystems. In Security and Privacy, 1980 IEEE Symposium on, pages 122-122. IEEE, 1980.
    [13]
    Satoshi Nakamoto. Bitcoin: A peer-to-peer electronic cash system. 2008.
    [14]
    Marc Pilkington. Blockchain technology: principles and applications. Research handbook on digital transformations, page 225, 2016.
    [15]
    Alex Rodriguez. Restful web services: The basics. IBM developer Works, page 33, 2008.
    [16]
    Reza Samavi and Mariano P Consens. Publishing l2tap logs to facilitate transparency and accountability. In LDOW, 2014.
    [17]
    Reza Samavi and Mariano P Consens. Publishing privacy logs to facilitate transparency and accountability. Journal of Web Semantics, 2018.
    [18]
    Craig Sayers and Alan H Karp. Computing the digest of an rdf graph. Mobile and Media Systems Laboratory, HP Laboratories, Palo Alto, USA, Tech. Rep. HPL-2003-235, 1, 2004.
    [19]
    Matthew Spoke. How blockchain tech will change auditing for good, 2015.
    [20]
    Vassilios Stathopoulos, Panayiotis Kotzanikolaou, and Emmanouil Magkos. Secure log management for privacy assurance in electronic communications. computers & security, 27(7-8):298-308, 2008.
    [21]
    Vipin Swarup, Len Seligman, and Arnon Rosenthal. A data sharing agreement framework. In International Conference on Information Systems Security, pages 22-36. Springer, 2006.
    [22]
    Yue Tong, Jinyuan Sun, Sherman SM Chow, and Pan Li. Cloud-assisted mobile-access of health data with privacy and auditability. IEEE Journal of biomedical and health Informatics, 18(2):419-429, 2014.
    [23]
    Daniel J Weitzner, Harold Abelson, Tim Berners-Lee, Joan Feigenbaum, James Hendler, and Gerald Jay Sussman. Information accountability. Communications of the ACM, 51(6):82-87, 2008.

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    Published In

    cover image Guide Proceedings
    IJCAI'18: Proceedings of the 27th International Joint Conference on Artificial Intelligence
    July 2018
    5885 pages
    ISBN:9780999241127

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    • IBMR: IBM Research
    • ERICSSON
    • Microsoft: Microsoft
    • AI Journal: AI Journal

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    AAAI Press

    Publication History

    Published: 13 July 2018

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