Security, Trust, and Privacy Management Framework in Cyber-Physical Systems using Blockchain

Das, Debashis; Banerjee, Sourav; Chatterjee, Pushpita; Ghosh, Uttam; Biswas, Utpal; Mansoor, Wathiq

doi:10.1109/ccnc51644.2023.10060483

Cited by 11 publications

(1 citation statement)

References 13 publications

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“…Cloud storage solutions provide flexibility and scalability for data storage, but they also introduce new issues for data management and security. Therefore, research and practice require continuous exploration and innovation to cope with the ever-changing technological environment and security threats [3] .…”

Section: Introductionmentioning

confidence: 99%

Research on data reliability and storage security verification for cloud platform based on machine learning

Wen,

Liu,

Ding

et al. 2024

Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024)

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At present, the data security and reliability of cloud storage are increasingly threatened by unreliable factors, resulting in major data security problems. As the data security of cloud platforms becomes increasingly prominent, this study starts with the current cybersecurity situation and the challenges of cloud data storage, and emphasizes the urgency of developing an efficient and reliable data verification mechanism. Subsequently, we propose a novel type of machine learning model that leverages advanced algorithms to identify and defend against potential threats of data breaches and corruption. In addition, we have verified the effectiveness of the model through a series of rigorous experiments, and the experimental results show that the model can not only accurately identify various security vulnerabilities, but also adapt to different cloud platform environments, and provide a strong guarantee in terms of data integrity and confidentiality.

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Section: Introductionmentioning

confidence: 99%

Research on data reliability and storage security verification for cloud platform based on machine learning

Wen,

Liu,

Ding

et al. 2024

Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024)

View full text Add to dashboard Cite

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Blockchain as a service environment: a dependability evaluation

2023

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Blockchain has become an important processing paradigm in recent years. The blockchain supports financial transactions and validates contracts, documents and data. However, the evolution of blockchain has become viable for many applications. The servers' availability and reliability (dependence) are required in the data processing. The contract will only be signed if there are enough components to form the blockchain blocks. This paper analyses the dependency between project components that use blockchain. We present a model based on stochastic Petri net (SPN) for evaluating the dependency of the blockchain architecture. The Design of Experiments (DoE) method was used to analyze this model's factors, seeking to know which ones had the higher impact on the system. The sensitivity analysis showed that the MongoDB component has a greater impact on the system dependency and the need to upgrade such a component. Also, for reliability, making component improvements is unnecessary if the system has fewer than 36,000 hours of runtime.

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A Mapping Review on Cyber-Physical Smart Contracts: Architectures, Platforms, and Challenges

et al. 2023

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Security, Trust, and Privacy Management Framework in Cyber-Physical Systems using Blockchain

Cited by 11 publications

References 13 publications

Research on data reliability and storage security verification for cloud platform based on machine learning

Research on data reliability and storage security verification for cloud platform based on machine learning

Blockchain as a service environment: a dependability evaluation

A Mapping Review on Cyber-Physical Smart Contracts: Architectures, Platforms, and Challenges

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