Risk Assessment and Analysis in Supply Chain Finance Based on Blockchain Technology

Meng, Xue

doi:10.1155/2022/1985803

Cited by 11 publications

(3 citation statements)

References 8 publications

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“…The prevalence of cyber threats, including sophisticated malware, ransomware attacks, phishing, and social engineering campaigns, has escalated in recent years, demanding advanced cybersecurity strategies to combat the complexity and variety of these attacks [24]. Data breaches in the finance sector not only led to financial losses but also undermined customer trust, emphasising the critical need for effective data protection measures.…”

Section: Existing Cybersecurity Challenges In the Finance Industrymentioning

confidence: 99%

Enhancing Zero Trust Models in the Financial Industry through Blockchain Integration: A Proposed Framework

Daah,

Qureshi,

Awan

et al. 2024

Electronics

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As financial institutions navigate an increasingly complex cyber threat landscape and regulatory ecosystem, there is a pressing need for a robust and adaptive security architecture. This paper introduces a comprehensive, Zero Trust model-based framework specifically tailored for the finance industry. It encompasses identity and access management (IAM), data protection, and device and network security and introduces trust through blockchain technology. This study provides a literature review of existing Zero Trust paradigms and contrasts them with cybersecurity solutions currently relevant to financial settings. The research adopts a mixed methods approach, combining extensive qualitative analysis through a literature review and assessment of security assumptions, threat modelling, and implementation strategies with quantitative evaluation using a prototype banking application for vulnerability scanning, security testing, and performance testing. The IAM component ensures robust authentication and authorisation processes, while device and network security measures protect against both internal and external threats. Data protection mechanisms maintain the confidentiality and integrity of sensitive information. Additionally, the blockchain-based trust component serves as an innovative layer to enhance security measures, offering both tamper-proof verification and increased integrity. Through analysis of potential threats and experimental evaluation of the Zero Trust model’s performance, the proposed framework offers financial institutions a comprehensive security architecture capable of effectively mitigating cyber threats and fostering enhanced consumer trust.

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Section: Existing Cybersecurity Challenges In the Finance Industrymentioning

confidence: 99%

Enhancing Zero Trust Models in the Financial Industry through Blockchain Integration: A Proposed Framework

Daah,

Qureshi,

Awan

et al. 2024

Electronics

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“…The mode adopted consensus mechanism to solve the problem of privacy protection of large credit data and realized access control and management of shared data chain. Xue [40] believed that blockchain technology can better protect the security of the financial industry, protect user privacy while mining data, evaluate the risks arising from SCF, and make corresponding analysis. Han et al [41] divided the SCF system into intelligent terminal layer, blockchain layer and application layer and put forward suggestions on the implementation of blockchain technology at each layer.…”

Section: Innovation Of Scf Modementioning

confidence: 99%

Prediction of Supply Chain Financial Credit Risk Based on PCA-GA-SVM Model

2022

Sustainability

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Supply Chain Finance (SCF) is a new type of financing business carried out by commercial banks on the basis of supply chain management, which effectively promotes the healthy development of the supply chain. As the most typical mode of SCF, accounts receivable financing mode can use the part of accounts receivable occupying working capital for financing, which is widely used. In order to effectively manage the credit risk in the Supply Chain Finance and maintain the healthy operation of the supply chain, this paper proposes a supply chain financial credit risk prediction model based on PCA-GA-SVM. First, principal component analysis (PCA) is used to reduce the dimension of the original index system, and then genetic algorithm (GA) is used to optimize the parameters of support vector machine (SVM). Finally, the principal components selected by PCA are input into the GA-SVM model for training, and the final prediction model is established. The running results show that the prediction performance of PCA-GA-SVM model is better than that of SVM and GA-SVM models. It has a good generalization ability, which can be used as a reference for commercial banks to improve the credit risk management ability of Supply Chain Finance and is conducive to the sustainable development of supply chain finance business.

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“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”

mentioning

confidence: 99%

Retracted: Risk Assessment and Analysis in Supply Chain Finance Based on Blockchain Technology

Sensors

2023

Journal of Sensors

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Risk Assessment and Analysis in Supply Chain Finance Based on Blockchain Technology

Cited by 11 publications

References 8 publications

Enhancing Zero Trust Models in the Financial Industry through Blockchain Integration: A Proposed Framework

Enhancing Zero Trust Models in the Financial Industry through Blockchain Integration: A Proposed Framework

Prediction of Supply Chain Financial Credit Risk Based on PCA-GA-SVM Model

Retracted: Risk Assessment and Analysis in Supply Chain Finance Based on Blockchain Technology

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