The CORAS Language – why it is designed the way it is

Solhaug, Bjørnar; Stølen, Ketil

doi:10.1201/b16387-456

Cited by 15 publications

(11 citation statements)

References 1 publication

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“…For capturing risk models, we chose CORAS because it has been empirically shown that the language is intuitively simple for stakeholders [27]. Apart from the indicators, we employed the standard CORAS language [2].…”

Section: Discussionmentioning

confidence: 99%

A Method for Developing Algorithms for Assessing Cyber-Risk Cost

Erdogan¹,

Gonzalez²,

Refsdal³

et al. 2017

2017 IEEE International Conference on Software Quality, Reliability and Security (QRS)

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Abstract-We present a method for developing executable algorithms for quantitative cyber-risk assessment. Exploiting techniques from security risk modeling and actuarial approaches, the method pragmatically combines use of available empirical data and expert judgments. The input to the algorithms are indicators providing information about the target of analysis, such as suspicious events observed in the network. Automated execution of the algorithms facilitates continuous assessment.

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Section: Discussionmentioning

confidence: 99%

A Method for Developing Algorithms for Assessing Cyber-Risk Cost

Erdogan¹,

Gonzalez²,

Refsdal³

et al. 2017

2017 IEEE International Conference on Software Quality, Reliability and Security (QRS)

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“…For this we use CORAS [60]. CORAS is an approach to risk analysis, supported by a graphical risk modelling language developed by Mass Soldal Lund et al We use CORAS as it has been empirically shown to be intuitively simple for different stakeholders, and has been proven to be cognitively effective [66]. CORAS comes with a method which builds on ISO 31000 [30], and includes detailed guidelines for creating CORAS risk models.…”

Section: Step 3 -Privacy and Security Risk Modellingmentioning

confidence: 99%

“…Developers don't always prioritize security, but they often need to consider security when developing software [110,111]. For capturing risk models, we chose CORAS because it has been empirically shown that the language is intuitively simple for stakeholders with different backgrounds [66]. We may therefore argue that the risk-model section of the tool is reasonably easy to understand by developers.…”

Section: Success Criterionmentioning

confidence: 99%

Tool Support for Risk-driven Planning of Trustworthy Smart IoT Systems within DevOps

Thompson

Erdogan

2020

Proceedings of the 6th International Conference on Information Systems Security and Privacy

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The Internet of Things is rising in popularity across many different domains, such as build automation, healthcare, electrical smart metering and physical security. Many prominent IT experts and companies like Gartner expect there to be a continued rise in the amount of IoT endpoints, with an estimated 5.8 million endpoints in 2020. With the rapid growth of the devices, the physical nature of these devices, and the amount of data collected, there will be a greater need for trustworthiness. These devices often gather personal data and as the devices have relatively less computational power than other devices, security and privacy risks are greater. With the IoT systems often operating in highly dynamic environments, the development of these systems should often be done in an iterative manner. De-vOps is an increasingly popular agile practice which combines the development and operations of systems to provide continuous delivery. This is well suited for the development of IoT systems. However, there is currently a lack of support for risk driven planning of trustworthy smart IoT systems within DevOps. This thesis investigates currently available tools and methods for the planning of trustworthy smart IoT systems within DevOps. We also propose a tool-supported method with the purpose of assisting developers in the planning phase of DevOps with identifying security and privacy risks, and executing risk assessment algorithms. Furthermore we facilitate automatic real-time security and privacy risk assessment through our custom made API. Moreover we conduct a case study where we apply both our method and tool in a real-life smart home case. Based on our initial result we argue that our tool-supported method: is easy to use and understandable for developers, supports the planning of trustworthy smart IoT systems in the DevOps practice in terms of security and privacy risk assessment and it is appropriate for use in the DevOps practice in terms of adapting to new plans and flexible in response to changes in the system.

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“…However, the graphical icons that are used to represent risk-related information in the CORAL language are based on corresponding graphical icons in the CORAS risk analysis language [91]. This is a deliberate design decision because the graphical icons in CORAS are empirically shown to be cognitively effective [139].…”

Section: Graphical Notationmentioning

confidence: 99%

Approaches for the combined use of risk analysis and testing: a systematic literature review

Erdogan

Runde

et al. 2014

Int J Softw Tools Technol Transfer

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The continuous increase of sophisticated cyber security risks exposed to the public, industry, and government through the web, mobile devices, social media, as well as targeted attacks via state-sponsored cyberespionage, clearly show the need for software security. Security testing is one of the most important practices to assure an acceptable level of security. However, security testers face the problem of determining the tests that are most likely to reveal severe security vulnerabilities. This is important in order to focus security testing on the most risky aspects of a system.In response to this challenge, the security testing community has proposed an approach to support security testing with security risk assessment (risk-driven security testing). In general, the purpose of risk-driven security testing is to focus the testing on the most severe security risks that the system under test is exposed to. However, current approaches carry out risk assessment at a high-level of abstraction (for example, business level) and then perform the testing accordingly. This is a disadvantage from a testing perspective because it leaves a gap between the risks and the test cases which are defined at a low-level of abstraction (for example, implementation level). This gap makes it difficult to identify exactly where in the system risks occur, and exactly how the risks should be tested. This also indicates that current approaches focus on risk-driven test planning at a high-level of abstraction for test management purposes, and do not necessarily focus on guiding the tester in designing test cases that have the ability to reveal vulnerabilities causing the most severe risks.This thesis proposes a model-based approach to risk-driven security testing, named CORAL, which is specifically developed to help security testers select and design test cases based on the available risk picture. The CORAL approach consists of seven steps supported by a risk analysis language. The risk analysis language is a modeling language based on UML interactions, and is formalized by an abstract syntax and a schematically defined natural-language semantics.As part of the development and evaluation process of the CORAL approach we carried out three industrial case studies. In the first two case studies, we investigated how risk assessment may be used to identify security test cases, as well as how security testing may be used to improve security risk analysis results. The experiences we obtained from these two industrial case studies helped us to, among other things, shape the CORAL approach. In the third case study we carried out the CORAL approach in an industrial setting in order to evaluate its applicability. The results indicate that CORAL supports security testers in producing risk models that are valid and directly testable. By directly testable risk models we mean risk models that can be reused and specified as test cases based on the interactions in the risk models. This, in turn, helps testers to select and design test cases according to t...

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The CORAS Language – why it is designed the way it is

Cited by 15 publications

References 1 publication

A Method for Developing Algorithms for Assessing Cyber-Risk Cost

A Method for Developing Algorithms for Assessing Cyber-Risk Cost

Tool Support for Risk-driven Planning of Trustworthy Smart IoT Systems within DevOps

Approaches for the combined use of risk analysis and testing: a systematic literature review

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