An Ontology Framework for Generating Discrete-Event Stochastic Models

Keefe, Ken; Feddersen, Brett; Rausch, Michael J.; Wright, Ronald Joseph; Sanders, William H.

doi:10.1007/978-3-030-02227-3_12

Cited by 4 publications

(1 citation statement)

References 23 publications

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“…ADVISE Meta [1] is an ontology framework for security analysis, which allows the automatic generation of complex, analyzable ADVISE [2] models starting from an architectural description of the system. In our two previous works [3], [4], we proposed a methodology that extends the ontology of ADVISE Meta with standardized adversaries' profiles and attack patterns, in order to enable a broader set of early-stage security analyses.…”

Section: Introductionmentioning

confidence: 99%

Modeling Moving Target Defense strategies and attacks with SAN and ADVISE

Mariotti,

Manetti,

Lollini

2023

2023 IEEE 34th International Symposium on Software Reliability Engineering Workshops (ISSREW)

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Security evaluation can be used at the early stage of development to identify the security level of the system's components and to guide the system's development process. In previous works we extended the ontology of ADVISE Meta, an highlevel security modeling framework, to integrate common attack patterns and standardized adversaries' profiles, thus enabling wide-ranging security analyses. However, in such formalism, the active part is played only by the adversary, while the defense is only a passive aspect delegated to a few embedded attributes of the models. This work proposes a preliminary study on an approach to model active dynamic defense strategies, known as Moving Target Defense (MTD). We target one of them, the proactive obfuscation technique, which is modeled using Stochastic Activity Networks to represent the system's dynamic defense and, we join it with an ADVISE model to represent the attack counterpart.

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Section: Introductionmentioning

confidence: 99%

Modeling Moving Target Defense strategies and attacks with SAN and ADVISE

Mariotti,

Manetti,

Lollini

2023

2023 IEEE 34th International Symposium on Software Reliability Engineering Workshops (ISSREW)

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CyberSAGE: The cyber security argument graph evaluation tool

Temple

Wu²,

Cheh³

et al. 2022

Empir Software Eng

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An extension of the ADVISE Meta modeling framework and its application for an early-stage security analysis of a public transport supervision system

Mariotti

Bondavalli

Lollini

et al. 2023

J Reliable Intell Environ

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Early-stage security analysis can be used for a preliminary assessment of the security level of a system, thus providing useful insights to guide the whole system’s development. In this paper, we focus on a specific meta-level modeling framework for security analysis, ADVISE Meta, which allows representing a system using generic built-in blocks and relationships constituting the ontology of the framework, and to automatically derive complex low-level stochastic models representing attack steps and adversaries. In this paper, we extend the ADVISE Meta ontology to enlarge the variety of the possible attack paths and adversaries that can be represented in the framework, by modeling (i) attack patterns available in the CAPEC database, a comprehensive dictionary of known patterns of attack, and (ii) the adversaries’ profiles defined in the Threat Agent Library (TAL), a reference library which describes the characteristics of threat agents. The paper provides a detailed description of the whole process for extending the ADVISE Meta ontology, and the application of the extended modeling framework for an early-stage security analysis of a public transport supervision system. The framework enables a variety of security-oriented analyses, in particular to assess the probability that a given adversary can successfully reach a specific goal, to analyze the most probable attack path that adversaries can follow to reach a goal, to perform sensitivity analysis at varying of attack patterns and adversaries’ profiles, to compare different architectural solutions, and to identify the system’s components that can be more probably attacked by adversaries.

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An Ontology Framework for Generating Discrete-Event Stochastic Models

Cited by 4 publications

References 23 publications

Modeling Moving Target Defense strategies and attacks with SAN and ADVISE

Modeling Moving Target Defense strategies and attacks with SAN and ADVISE

CyberSAGE: The cyber security argument graph evaluation tool

An extension of the ADVISE Meta modeling framework and its application for an early-stage security analysis of a public transport supervision system

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