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Abstract Interpretation of Stateful Networks

  • Kalev Alpernas
  • , Roman Manevich
  • , Aurojit Panda
  • , Mooly Sagiv
  • , Scott Shenker
  • , Sharon Shoham
  • , Yaron Velner

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

    11 Scopus citations

    Abstract

    Modern networks achieve robustness and scalability by maintaining states on their nodes. These nodes are referred to as middleboxes and are essential for network functionality. However, the presence of middleboxes drastically complicates the task of network verification. Previous work showed that the problem is undecidable in general and EXPSPACE-complete when abstracting away the order of packet arrival. We describe a new algorithm for conservatively checking isolation properties of stateful networks. The asymptotic complexity of the algorithm is polynomial in the size of the network, albeit being exponential in the maximal number of queries of the local state that a middlebox can do, which is often small. Our algorithm is sound, i.e., it can never miss a violation of safety but may fail to verify some properties. The algorithm performs on-the fly abstract interpretation by (1) abstracting away the order of packet processing and the number of times each packet arrives, (2) abstracting away correlations between states of different middleboxes and channel contents, and (3) representing middlebox states by their effect on each packet separately, rather than taking into account the entire state space. We show that the abstractions do not lose precision when middleboxes may reset in any state. This is encouraging since many real middleboxes reset, e.g., after some session timeout is reached or due to hardware failure.

    Original languageEnglish
    Title of host publicationStatic Analysis - 25th International Symposium, SAS 2018, Proceedings
    EditorsAndreas Podelski
    PublisherSpringer Verlag
    Pages86-106
    Number of pages21
    ISBN (Print)9783319997247
    DOIs
    StatePublished - 1 Jan 2018
    Event25th International Static Analysis Symposium, SAS 2018 - Freiburg, Germany
    Duration: 29 Aug 201831 Aug 2018

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume11002 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference25th International Static Analysis Symposium, SAS 2018
    Country/TerritoryGermany
    CityFreiburg
    Period29/08/1831/08/18

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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