An Attacker Modeling Framework for the Assessment of Cyber-Physical Systems Security

Deloglos, Christopher; Elks, Carl; Tantawy, Ashraf

doi:10.1007/978-3-030-54549-9_10

Cited by 12 publications

(4 citation statements)

References 15 publications

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“…To detect the malicious attack in the network, prevent the attack on the system and resources, and preserve sensitive information from cybercriminal activities of the network, various approaches are implemented ( Disha & Waheed, 2022 ). Cyber-physical systems (CPS) have been implemented in connecting different sensor-based devices, IoT-based devices, and robots where information is collected from multiple terminal devices in heterogeneous data ( Deloglos, Elks & Tantawy, 2020 ; Li et al, 2022 ). The KDD 99 and NSLKDD 99 datasets identify cyber-attacks in the cyber-physical system ( Thomas & Pavithran, 2018 ; Li et al, 2021 ).…”

Section: Review Of Literaturementioning

confidence: 99%

Emerging framework for attack detection in cyber-physical systems using heuristic-based optimization algorithm

Alohali,

Elsadig,

Hilal

et al. 2023

PeerJ Computer Science

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In recent days, cyber-physical systems (CPS) have become a new wave generation of human life, exploiting various smart and intelligent uses of automotive systems. In these systems, information is shared through networks, and data is collected from multiple sensor devices. This network has sophisticated control, wireless communication, and high-speed computation. These features are commonly available in CPS, allowing multi-users to access and share information through the network via remote access. Therefore, protecting resources and sensitive information in the network is essential. Many research works have been developed for detecting insecure networks and attacks in the network. This article introduces a framework, namely Deep Bagging Convolutional Neural Network with Heuristic Multiswarm Ant Colony Optimization (DCNN-HMACO), designed to enhance the secure transmission of information, improve efficiency, and provide convenience in Cyber-Physical Systems (CPS). The proposed framework aims to detect attacks in CPS effectively. Compared to existing methods, the DCNN-HMACO framework significantly improves attack detection rates and enhances overall system protection. While the accuracy rates of CNN and FCM are reported as 72.12% and 79.56% respectively, our proposed framework achieves a remarkable accuracy rate of 92.14%.

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Section: Review Of Literaturementioning

confidence: 99%

Emerging framework for attack detection in cyber-physical systems using heuristic-based optimization algorithm

Alohali,

Elsadig,

Hilal

et al. 2023

PeerJ Computer Science

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“…Based on an enterprise architecture, it calculates how secure a system is by using the likelihood of successful attacks. [4], [27] or Deloglos et al [28] provide an attack path calculation approach. They also use various attack classifications as a basis.…”

Section: A Attack Modelling and Analysismentioning

confidence: 99%

Automatic Derivation of Vulnerability Models for Software Architectures

Kirschner

Walter

Bossert

et al. 2023

2023 IEEE 20th International Conference on Software Architecture Companion (ICSA-C)

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Software architectures consist of more and more connections to different components or elements. With the increased connection and exchange between different elements also the attack surface increases, since each element might contain vulnerabilities. The vulnerabilities may be harmless on their own, but attackers could develop attack paths from the combination of different vulnerabilities. For a model-based attack propagation analysis, it is useful to have an annotated components model with vulnerabilities. However, depending on the size of the system, the manual annotation of these models is very time-consuming and error-prone. In this context, we present in this paper an approach that automatically annotates vulnerability information to the components of an architectural model. The goal here is to extract security information of source artifacts and transform them into an existing architecture-based security model to enable modelbased security risk assessment. We evaluate our approach using three open-source case studies to demonstrate feasibility and accuracy. The results indicate high recall reading vulnerabilities.

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“…However, determining the initial values for the probability of an attack is quite cumbersome, and so far, the propagation does not consider dynamic access policies like ABAC [5]. Approaches such as [39], [40] or Deloglos et al [41] reuse existing vulnerability classifications to calculate the attack paths. However, so far they do not explicitly consider access control policies.…”

Section: State Of the Artmentioning

confidence: 99%

Architectural Attack Propagation Analysis for Identifying Confidentiality Issues

Walter

Heinrich

Reussner

2022

2022 IEEE 19th International Conference on Software Architecture (ICSA)

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Exchanging data between different systems enables us to build new smart services and digitise various areas of our daily life. This digitalisation leads to more efficient usage of resources, and an increased monetary value. However, the connection of different systems also increases the number of potential vulnerabilities. The vulnerabilities on their own might be harmless, but attackers could build attack paths based on the combination of different vulnerabilities. Additionally, attackers might exploit existing access control policies to further propagate through the system. For analysing this dependency between vulnerabilities and access control policies, we extended an architecture description language (ADL) to model access control policies and specify vulnerabilities. We developed an attack propagation analysis operating on the extended ADL, which can help to determine confidentiality violations in a system. We evaluated our approach by analysing the accuracy and the effort compared to a manual analysis using different scenarios in three case studies. The results indicate that our analysis is capable of identifying attack paths and reducing the effort compared to manual detection.

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An Attacker Modeling Framework for the Assessment of Cyber-Physical Systems Security

Cited by 12 publications

References 15 publications

Emerging framework for attack detection in cyber-physical systems using heuristic-based optimization algorithm

Emerging framework for attack detection in cyber-physical systems using heuristic-based optimization algorithm

Automatic Derivation of Vulnerability Models for Software Architectures

Architectural Attack Propagation Analysis for Identifying Confidentiality Issues

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