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.

Conti V., Ziggiotto A., Migliardi M., Vitabile S. (2020). Bio-inspired security analysis for IoT scenarios. INTERNATIONAL JOURNAL OF EMBEDDED SYSTEMS, 13(2), 221-235 [10.1504/IJES.2020.108871].

Bio-inspired security analysis for IoT scenarios

Vitabile S.
2020-01-01

Abstract

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.
2020
Conti V., Ziggiotto A., Migliardi M., Vitabile S. (2020). Bio-inspired security analysis for IoT scenarios. INTERNATIONAL JOURNAL OF EMBEDDED SYSTEMS, 13(2), 221-235 [10.1504/IJES.2020.108871].
File in questo prodotto:
File Dimensione Formato  
CONTI_241416_Preprint.pdf

accesso aperto

Descrizione: Pre-print dell'articolo
Tipologia: Pre-print
Dimensione 1.62 MB
Formato Adobe PDF
1.62 MB Adobe PDF Visualizza/Apri
IJES130210 CONTI_241416.pdf

Solo gestori archvio

Descrizione: Versione editoriale dell'articolo
Tipologia: Versione Editoriale
Dimensione 1.65 MB
Formato Adobe PDF
1.65 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/436681
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 2
social impact