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Item type:Publication, Access status: with files , Checking security compliance between models and code(Springer, 2023-02); ; ; ; It is challenging to verify that the planned security mechanisms are actually implemented in the software. In the context of model-based development, the implemented security mechanisms must capture all intended security properties that were considered in the design models. Assuring this compliance manually is labor intensive and can be error-prone. This work introduces the first semi-automatic technique for secure data flow compliance checks between design models and code. We develop heuristic-based automated mappings between a design-level model (SecDFD, provided by humans) and a code-level representation (Program Model, automatically extracted from the implementation) in order to guide users in discovering compliance violations, and hence, potential security flaws in the code. These mappings enable an automated, and project-specific static analysis of the implementation with respect to the desired security properties of the design model. We developed two types of security compliance checks and evaluated the entire approach on open source Java projects.Publicationtype: Journal ArticleScopus© Citations 3 68 116 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Secure Data-Flow Compliance Checks between Models and Code Based on Automated MappingsDuring the development of security-critical software, the system implementation must capture the security properties postulated by the architectural design. This paper presents an approach to support secure data-flow compliance checks between design models and code. To iteratively guide the developer in discovering such compliance violations we introduce automated mappings. These mappings are created by searching for correspondences between a design-level model (Security Data Flow Diagram) and an implementation-level model (Program Model). We limit the search space by considering name similarities between model elements and code elements as well as by the use of heuristic rules for matching data-flow structures. The main contributions of this paper are three-fold. First, the automated mappings support the designer in an early discovery of implementation absence, convergence, and divergence with respect to the planned software design. Second, the mappings also support the discovery of secure data-flow compliance violations in terms of illegal asset flows in the software implementation. Third, we present our implementation of the approach as a publicly available Eclipse plugin and its evaluation on five open source Java projects (including Eclipse secure storage).Publicationtype: Conference Paper29