Semantic model for action-based adaptive security

Sara Sartoli, Akbar Siami Namin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

This paper presents a semantic model to represent topology-based security requirements, recommend measures to address any possible security violations, and thus make the underlying systems compliant with its security requirements. The proposed actionbased model is capable of adaptively adjusting the topological model of a given system in response to changes in the structure of its operational environment. The proposed framework benefits from non-monotonic reasoning to reason about possible execution paths and hence recommend actions to prevent security requirements violations. The results of our case studies show that using the proposed approach to enforce security measures, not only can we detect possible security violations caused by changes in the structure of operational environment, but also recommend actions to address possible violations.

Original languageEnglish
Title of host publication32nd Annual ACM Symposium on Applied Computing, SAC 2017
PublisherAssociation for Computing Machinery
Pages1130-1135
Number of pages6
ISBN (Electronic)9781450344869
DOIs
StatePublished - Apr 3 2017
Event32nd Annual ACM Symposium on Applied Computing, SAC 2017 - Marrakesh, Morocco
Duration: Apr 4 2017Apr 6 2017

Publication series

NameProceedings of the ACM Symposium on Applied Computing
VolumePart F128005

Conference

Conference32nd Annual ACM Symposium on Applied Computing, SAC 2017
CountryMorocco
CityMarrakesh
Period04/4/1704/6/17

Keywords

  • Access control
  • Adaptive security
  • Answer set programming
  • Formal methods
  • Topology Awareness

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  • Cite this

    Sartoli, S., & Namin, A. S. (2017). Semantic model for action-based adaptive security. In 32nd Annual ACM Symposium on Applied Computing, SAC 2017 (pp. 1130-1135). (Proceedings of the ACM Symposium on Applied Computing; Vol. Part F128005). Association for Computing Machinery. https://doi.org/10.1145/3019612.3019755