6533b86ffe1ef96bd12ce885
RESEARCH PRODUCT
Bio-inspired security analysis for IoT scenarios
Vincenzo ContiAndrea ZiggiottoMauro MigliardiSalvatore Vitabilesubject
Bio-inspired techniqueService (systems architecture)Security analysisIoTDependency (UML)Computer scienceNetwork securityDistributed computingmedia_common.quotation_subject0211 other engineering and technologies02 engineering and technologyMetabolic networksAttack graphs; Bio-inspired algorithms; Bio-inspired techniques; IoT; Metabolic networks; Network security; Security analysis; System securityAttack graph03 medical and health sciences0302 clinical medicineUse casemedia_common021110 strategic defence & security studiesSecurity analysisbusiness.industryMetabolic network030208 emergency & critical care medicineBio-inspired techniquesNetwork securitySystem securityFlux balance analysisInterdependenceHardware and ArchitectureBio-inspired algorithmGraph (abstract data type)businessSoftwareAttack graphsBio-inspired algorithmsdescription
Computer security has recently become more and more important as the world economy dependency from data has kept growing. The complexity of the systems that need to be kept secure calls for new models capable of abstracting the interdependencies among heterogeneous components that cooperate at providing the desired service. A promising approach is attack graph analysis, however, the manual analysis of attack graphs is tedious and error prone. In this paper we propose to apply the metabolic network model to attack graph analysis, using three interacting bio-inspired algorithms: topological analysis, flux balance analysis, and extreme pathway analysis. A developed framework for graph building and simulations as well as an introductory to some IoT scenarios as use cases are also outlined.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2020-01-01 |