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Item type:Publication, Access status: without files , In specs we trust? Conformance-analysis of implementation to specifications in Node-RED and associated security risksLow-code development frameworks for IoT platforms offer a simple drag-and-drop mechanism to create applications for the billions of existing IoT devices without the need for extensive programming knowledge. The security of such software is crucial given the close integration of IoT devices in many highly sensitive areas such as healthcare or home automation. Node-RED is a framework to build applications from nodes that are contributed by open-source developers. Its reliance on unvetted contributions and lack of security checks raises the concern that the applications could be vulnerable to attacks, thereby posing a security risk to end users. The low-code approach could imply that users lack the technical knowledge to mitigate or even realize such security concerns. This paper focuses on hidden information flows in Node-RED nodes, meaning flows that are not captured by the specifications. They could (unknowingly or with malicious intent) cause leaks of sensitive information to unauthorized entities. We report the results of a conformance analysis of all nodes in the Node-RED framework, for which we compared the numbers of specified inputs and outputs of each node against the number of sources and sinks detected with CodeQL. The results show, that 55% of all nodes exhibit more possible flows than are specified. A risk assessment of a subset of the nodes showed, that 28% of them are associated with a high severity and 36% with a medium severity rating.Publicationtype: Conference Paper21 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Designing secure AI-based systems: a multi-vocal literature review(IEEE, 2024-10); ; ; AI-based systems leverage recent advances in the field of AI/ML by combining traditional software systems with AI components. Applications are increasingly being developed in this way. Software engineers can usually rely on a plethora of supporting information on how to use and implement any given technology. For AI-based systems, however, such information is scarce. Specifically, guidance on how to securely design the architecture is not available to the extent as for other systems.We present 16 architectural security guidelines for the design of AI-based systems that were curated via a multi-vocal literature review. The guidelines could support practitioners with actionable advice on the secure development of AI-based systems. Further, we mapped the guidelines to typical components of AI-based systems and observed a high coverage where 6 out of 8 generic components have at least one guideline associated to them.Publicationtype: Conference Paper16 - Some of the metrics are blocked by yourconsent settings
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 68 115 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Precise Analysis of Purpose Limitation in Data Flow DiagramsData Flow Diagrams (DFDs) are primarily used for modelling functional properties of a system. In recent work, it was shown that DFDs can be used to also model non-functional properties, such as security and privacy properties, if they are annotated with appropriate security- and privacy-related information. An important privacy principle one may wish to model in this way is purpose limitation. But previous work on privacy-aware DFDs (PA-DFDs) considers purpose limitation only superficially, without explaining how the purpose of DFD activators and flows ought to be specified, checked or inferred. In this paper, we define a rigorous formal framework for (1) annotating DFDs with purpose labels and privacy signatures, (2) checking the consistency of labels and signatures, and (3) inferring labels from signatures. We implement our theoretical framework in a proof-of concept tool consisting of a domain-specific language (DSL) for specifying privacy signatures and algorithms for checking and inferring purpose labels from such signatures. Finally, we evaluate our framework and tool through a case study based on a DFD from the privacy literature.Publicationtype: Conference Paper36 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Finding security threats that matter: Two industrial case studiesIn the past decade, speed has become an essential trait of software development (e.g., agile, continuous integration, DevOps) and any inefficiency is considered unaffordable time waster. Such a fast pace causes challenges for architectural threat analysis. Leading techniques for threat analysis, like STRIDE, have the advantage of being systematic. However, they are not equipped to discern between important and less critical threats, while the threats are being discovered. Consequently, many threats are discarded at a later time, when their risk value is assessed. An alternative technique, called eSTRIDE, promises to remove these inefficiencies by focusing the analysis on the critical parts of the architecture. Yet, no empirical evidence exists about the actual effect of trading off systematicity, for a more focused attention on high-priority threats. This paper contributes with an empirical study comparing these two approaches in the context of two industrial case studies. We found that the two approaches yield the same number of security threats during a given time frame. However, participants using eSTRIDE found twice as many high-priority threats. The underlying analysis procedures cause similarities and differences in the execution. In addition, security expertise has an effect (albeit small) on the quality of analysis outcomes and execution.Publicationtype: Journal Article66 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Automating the early detection of security design flaws(2020-10-16); ; ; Security by design is a key principle for realizing secure software systems and it is advised to hunt for security flaws from the very early stages of development. At design-time, security analysis is often performed manually by means of either threat modeling or expert-based design inspections. However, when leveraging the wide range of established knowledge bases on security design flaws (e.g., CWE, CAWE), these manual assessments become too time consuming, error-prone, and infeasible in the context of contemporary development practices with frequent iterations. This paper focuses on design inspection and explores the potential for automating the application of inspection rules to speed up the security analysis. The contributions of this paper are: (i) the creation of a publicly available data set consisting of 26 design models annotated with security flaws, (ii) an automated approach for following inspection guidelines using model query patterns, and (iii) an empirical comparison of the results from this automated approach with those from manual inspection. Even though our results show that a complete automation of the security design flaw detection is hard to achieve, we find that some flaws (e.g., insecure data exposure) are more amenable to automation. Compared to manual analysis techniques, our results are encouraging and suggest that the automated technique could guide security analysts towards a more complete inspection of the software design, especially for large models.Publicationtype: Conference Paper60 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Towards automated security design flaw detection(2019-11); ; ; ; Efficiency of security-by-design has become an important goal for organizations implementing software engineering practices such as Agile, DevOps, and Continuous Integration. Software architectures are (often manually) analyzed at design time for potential security design flaws, based on natural language descriptions of security weaknesses (e.g., CWE, CAPEC). The use of natural language hinders the application of such knowledge bases in an automated fashion. In this paper, we analyze an existing catalog of 19 security design flaws in order to identify conceptual, technology-independent requirements on architectural models that enable automatically detecting these flaws. This constitutes the first step towards automated assessment of design-level security. Our findings are illustrated on an IoT-based smart home system.Publicationtype: Conference Paper25 - 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 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Inspection guidelines to identify security design flaws(Association for Computing Machinery (ACM), 2019-09); ; ; Recent trends in the software development practices (Agile, De-vOps, CI) have shortened the development life-cycle causing the need for efficient security-by-design approaches. In this context, software architectures are analyzed for potential vulnerabilities and design flaws. Yet, design flaws are often documented with natural language and require a manual analysis, which is inefficient. Besides low-level vulnerability databases (e.g., CWE, CAPEC) there is little systematized knowledge on security design flaws. The purpose of this work is to present and evaluate a catalog of security design flaws accompanied by inspection guidelines for their detection. To this aim, we conduct empirical studies with master and doctoral students. This paper presents a catalog of 19 inspection guidelines for detecting security design flaws and contributes with an empirical evaluation of the inspection guidelines. We also account for the shortcomings of the inspection guidelines and make suggestions for their improvement with respect to the generalization of guidelines, catalog re-organization, and format of documentation. We record similar precision, recall, and productivity in both empirical studies.Publicationtype: Conference Paper27 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Flaws in Flows: Unveiling design flaws via information flow analysis(2019-03); ; This paper presents a practical and formal approach to analyze security-centric information flow policies at the level of the design model. Specifically, we focus on data confidentiality and data integrity objectives. In its guiding principles, the approach is meant to be amenable for designers (e.g., software architects) that have very limited or no background in formal models, logics, and the like. To this aim, we provide an intuitive graphical notation, which is based on the familiar Data Flow Diagrams, and which requires as little effort as possible in terms of extra security-centric information the designer has to provide. The result of the analysis algorithm is the early discovery of design flaws in the form of violations of the intended security properties. The approach is implemented as a publicly available plugin for Eclipse and evaluated with four real-world case studies from publicly available literature.Publicationtype: Conference Paper31