Fog Computing Over IoT: A Secure Deployment and Formal Verification

Zahra, Samman; Alam, Mansaf; Javaid, Qaisar; Wahid, Abdul; Javaid, Nadeem; Malik, Saif Ur Rehman; Khan, Muhammad Khurram

doi:10.1109/access.2017.2766180

Cited by 38 publications

(21 citation statements)

References 40 publications

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“…c) Access Control Based on Other Technology: Other ways were explored to implement access control in edge computing. For secure data outsourcing and access, Zahra et al [89] focused on adding the Shibboleth protocol in a fog-IoT network to achieve cross domain data access control between user devices and fog nodes. The authors detailly introduced the workflow of the Shibboleth system and further demonstrated its correctness.…”

Section: Secure Data Storage In Edge Computingmentioning

confidence: 99%

A Survey on Secure Data Analytics in Edge Computing

Liú

Yan

Ding

et al. 2019

IEEE Internet Things J.

145

103

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Internet of Things (IoT) is gaining increasing popularity. Overwhelming volumes of data are generated by IoT devices. Those data after analytics provide significant information that could greatly benefit IoT applications. Different from traditional applications, IoT applications such as environmental monitoring, smart navigation and smart healthcare come with new requirements such as mobility, real-time response, and location awareness. However, traditional cloud computing paradigm cannot satisfy these demands due to centralized processing and being far away from local devices. Hence, edge computing was introduced to perform data processing and storage in the edge of networks, which is closer to data sources than cloud computing, thus efficient and location-aware. Unfortunately, edge computing brings new security and privacy challenges when applied to data analytics. The literature still lacks a thorough review on the recent advances in secure data analytics in edge computing. In this paper, we first introduce the concept and features of edge computing, and then propose a number of requirements for its secure data analytics by analyzing potential security threats in edge computing. Furthermore, we give a comprehensive review on the pros and cons of the existing works on data analytics in edge computing based on our proposed requirements. Based on our literature survey, we highlight current open issues and propose future research directions.

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Section: Secure Data Storage In Edge Computingmentioning

confidence: 99%

A Survey on Secure Data Analytics in Edge Computing

Liú

Yan

Ding

et al. 2019

IEEE Internet Things J.

145

103

View full text Add to dashboard Cite

show abstract

“…Zahra et al [19] examine the security of data communication within Fog-IoT systems. The authors introduced a mechanism to strengthen the communication security and formally verify it against a set of security properties.…”

Section: Related Workmentioning

confidence: 99%

Towards Formally Verified Key Management for Industrial Control Systems

Kulik

Boudjadar

Aranha

2020

Proceedings of the 8th International Conference on Formal Methods in Software Engineering

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Adoption of new digital technologies is impacting all aspects of society. While these new technologies are accepted rapidly within the consumer segment, in the area of industrial control systems the pace of change in computing is slower. This is often due to the criticality and security constraints of such systems, since degraded or hijacked control could lead to injuries or competitive disadvantages. Nowadays a critical component of control systems is the key management protocol for protecting communication. This is specifically important as more and more devices become part of industrial control networks. The key management system must be reliable and robust in order to ensure stable operation of the system with minimum downtime. This often means that the system needs to be autonomous and dynamic, capable of periodically changing the keys automatically and authenticating the system components. Different techniques have been used to examine the reliability and robustness of the key management systems, one promising approach is by using formal methods. In this paper we present a formally verified key management system for use within distributed industrial control systems. We demonstrate that the key management system can reliably handle authentication/communication operations in real-time as well as joining/leaving of control units within the system. We use UPPAAL to analyse several security properties, showing that our models satisfy a collection of requirements defined by our industrial partner and are viable for dynamic key management applications.

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“…Security has also been the subject of the application of formal verification t echniques i n t he c ontext o f I ndustry 4.0 systems, particularly when it comes to the issue of the integration of various system components. In [36], for example, the Shibboleth federated identity and single-sign on protocol [37] was proposed as a solution to securely connect Fog clients and Fog nodes [38] in automation systems. High-level Petri nets [39] were then used to demonstrate the reliability and robustness of this connection.…”

Section: Related Workmentioning

confidence: 99%

Modeling and Analyzing an Industry 4.0 Communication Protocol

Aziz

2020

IEEE Internet Things J.

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The increasing complexity and criticality of industrial automation systems, embodied by the concept of Industry 4.0, which brings together concepts like Cyber-physical systems, the Internet-of-Things, Big Data and Artificial Intelligence, calls for more formality in specifying the technology standards underlying these systems. We define in this paper a formal model of an Industry 4.0 machine-2-machine communication protocol, Hermes, used in specifying electronic board transfers in an assembly line. Our analysis of the formal specification reveals that, despite the robustness of the protocol, many testing scenarios have been ignored in the protocol standard and in particular, scenarios that include simultaneous machine errors. Therefore, our work paves the way for a better informed testing strategy in Industry 4.0 systems that implement the protocol.

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Fog Computing Over IoT: A Secure Deployment and Formal Verification

Cited by 38 publications

References 40 publications

A Survey on Secure Data Analytics in Edge Computing

A Survey on Secure Data Analytics in Edge Computing

Towards Formally Verified Key Management for Industrial Control Systems

Modeling and Analyzing an Industry 4.0 Communication Protocol

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