Four Dimensional Security and Vulnerability Matrix for Cloud (4-SVM)

Dey, Sharmistha; Sen, Santanu

doi:10.15439/2017r41

Cited by 4 publications

(1 citation statement)

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“…An attacker can also execute a malware attack to alter data, obtain control, or execute malicious code by injecting a malicious service instance or a virtual machine into the cloud [51]. This allows the attacker access to confidential data [52]. In the authentication attack [53], an attacker uses the vulnerabilities present in the cloud services (such as a single-factor authentication process or weak password) to disrupt the cloud services or steal confidential information.…”

Section: Virtual Layermentioning

confidence: 99%

Security Analysis of a Digital Twin Framework Using Probabilistic Model Checking

et al. 2023

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Digital Twins (DTs) have been gaining popularity in various applications, such as smart manufacturing, smart energy, smart mobility, and smart healthcare. In simple terms, DT is described as a virtual replica of a given physical product, system, or process. It consists of three major segments: the physical entity, its virtual counterpart, and the connections between them. While the data is collected from a physical entity, processed at the virtual layer, and accessed in the form of a DT at the application layer, it is exposed to several security risks. To ensure the applicability of a DT system, it is imperative to understand these security risks and their implications. However, there is a lack of a framework that can be used to assess the security of a DT. This paper presents a framework in which the security of a DT can be analyzed with the help of a formal verification technique. The framework captures the defense of the system at different layers and considers various attacks at each layer. The security of the DT system is represented as a statetransition system and the security properties are captured in temporal logic. Probabilistic model checking (PMC) is used to verify the systems against these properties. In particular, the framework is used to analyze the probability of success and the cost of various potential attacks that can occur at each layer in a DT system. The applicability of the proposed framework is demonstrated with the help of a detailed case study in the healthcare domain.INDEX TERMS Digital twin security, security analysis, probabilistic model checking, Markov decision process, discrete time Markov chain.

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Section: Virtual Layermentioning

confidence: 99%