Zerber: r-Confidential Indexing for Distributed Documents

Sergej Zerr, Elena Demidova, Daniel Olmedilla, Wolfgang Nejdl, Marianne Winslett, Soumyadeb Mitra

    Research output: Chapter in Book/Report/Conference proceedingConference Article in proceedingAcademicpeer-review


    To carry out work assignments, small groups distributed within a larger enterprise often need to share documents among themselves while shielding those documents from others’ eyes. In this situation, users need an indexing facility that can quickly locate relevant documents that they are allowed to access, without (1) leaking information about the remaining documents, (2) imposing a large management burden as users, groups, and documents evolve, or (3) requiring users to agree on a central completely trusted authority. To address this problem, we propose the concept of r-confidentiality, which captures the degree of information leakage from an index about the terms contained in inaccessible documents. Then we propose the r-confidential Zerber indexing facility for sensitive documents, which uses secret splitting and term merging to provide tunable limits on information leakage, even under statistical attacks; requires only limited trust in a central indexing authority; and is extremely easy to use and administer. Experiments with real-world data show that Zerber offers excellent performance for index insertions and lookups while requiring only a modest amount of storage space and network bandwidth
    Original languageEnglish
    Title of host publicationZerber: r-Confidential Indexing for Distributed Documents
    Publication statusPublished - 25 Mar 2008

    Publication series

    SeriesDefault journal


    • secure inverted index
    • information sharing
    • database
    • security


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