Security Challenges of Blockchain-Based Supply Chain Systems

Ismail, Shereen; Reza, Hassan

doi:10.1109/uemcon54665.2022.9965682

Cited by 7 publications

(3 citation statements)

References 27 publications

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“…BC is a Distributed Ledger Technology (DLT) that can be used as a decentralized database that supports the essential SC system requirements, including visibility, provenance, security, and traceability [5,6]. New technological advancements, such as Big Data, Artificial Intelligence (AI), and Internet of Things (IoT), integrated with BC-based seafoodSCs, can offer significant advantages and create an agile and effective ecosystem [7], revolutionizing how smart cities manage their perishable food supplies and enhance seafood safety measures [8].…”

Section: Introductionmentioning

confidence: 99%

A Blockchain-Based Fish Supply Chain Framework for Maintaining Fish Quality and Authenticity

Ismail,

Nouman,

Reza

et al. 2024

Preprint

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The fish supply chain (FSC) industry faces a significant challenge in terms of maintaining fish quality and authenticity throughout the chain. The main goal of modern FSC systems is tracking and tracing the fish product at each stage, from harvester to end customer, as well as assessing its quality and authenticity. Integrating FSC with new technologies, such as Blockchain (BC), Big Data, Artificial intelligence (AI), and Internet of Things (IoT), enhances fish product traceability, authenticity, visibility, and security. We propose a BC-based FSC framework that follows a layered architecture consisting of a SC layer, an IoT layer, and a BC layer. We integrate a new AI-based hand-held device, a Quality, Adulteration & Traceability (QAT) device, that can identify fish species and assess fish quality. We leverage the key features of BC and smart contracts, deployed over the Ethereum platform for the proposed framework integrated with QAT technology. Extensive validation of smart contracts is conducted to prove its practical feasibility.

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Section: Introductionmentioning

confidence: 99%

A Blockchain-Based Fish Supply Chain Framework for Maintaining Fish Quality and Authenticity

Ismail,

Nouman,

Reza

et al. 2024

Preprint

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“…For example, a 2017 NotPetya ransomware SC attack, which focused on encrypting and locking data for ransom rather than stealing it [1]. Additionally, the SolarWinds sunburst attack in 2020 compromised numerous companies globally, gaining unauthorized access to sensitive data for thousands of customers [2].. The sprawling interconnections within contemporary SC systems, encompassing a multitude of stakeholders, technologies, and geographies, introduce vulnerabilities that malicious actors can exploit.…”

Section: Introductionmentioning

confidence: 99%

Blockchain-Based Zero Trust Supply Chain Security Integrated with Deep Reinforcement Learning

Ismail,

Moudoud,

Dawoud

et al. 2024

Preprint

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The modern supply chain (SC) is growing in terms of data, devices, users, and stakeholders, which introduced new security challenges and threats, especially with the reliance on centralized servers or cloud platforms. In addition, increased trust among system participants exposes the SC to a higher risk of vulnerabilities which require strong security measures. This article proposes a hybrid security framework for SC systems, BC-DRLzSC, that integrates Blockchain (BC) and Deep Reinforcement Learning (DRL) designed to operate in a zero trust (ZT) environment. In particular, we propose a decentralized BC-based approach integrated with smart contracts to manage system participant registration and authentication and to control access to system resources. BC-DRLzSC adopts a ZT architecture to reinforce SC security, which can be achieved with an advocate to verify each entity’s trustworthiness before granting or retaining access to system resources. Incorporating the ZT architecture, with BC and DRL, can potentially and significantly bolster SC system security. DRL is employed to develop a proactive attack detection model that continuously monitors the incoming traffic from authenticated nodes within the network and predicts any malicious actions. Finally, we evaluate the performance of our proposed DRL solution using the NSL-KDD dataset.

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“…These traditional approaches often focus on specific application scenarios and may struggle to adapt to the complex and dynamic nature of modern supply chains [6]. Furthermore, these methods often lack the ability to effectively handle the vast amounts of data generated in modern supply chains, limiting their potential for real-time optimization and risk mitigation [7].…”

Section: Introductionmentioning

confidence: 99%

Blockchain-Based Zero-Trust Supply Chain Security Integrated with Deep Reinforcement Learning for Inventory Optimization

Ma,

Chen,

Sun

et al. 2024

Future Internet

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Modern supply chain systems face significant challenges, including lack of transparency, inefficient inventory management, and vulnerability to disruptions and security threats. Traditional optimization methods often struggle to adapt to the complex and dynamic nature of these systems. This paper presents a novel blockchain-based zero-trust supply chain security framework integrated with deep reinforcement learning (SAC-rainbow) to address these challenges. The SAC-rainbow framework leverages the Soft Actor–Critic (SAC) algorithm with prioritized experience replay for inventory optimization and a blockchain-based zero-trust mechanism for secure supply chain management. The SAC-rainbow algorithm learns adaptive policies under demand uncertainty, while the blockchain architecture ensures secure, transparent, and traceable record-keeping and automated execution of supply chain transactions. An experiment using real-world supply chain data demonstrated the superior performance of the proposed framework in terms of reward maximization, inventory stability, and security metrics. The SAC-rainbow framework offers a promising solution for addressing the challenges of modern supply chains by leveraging blockchain, deep reinforcement learning, and zero-trust security principles. This research paves the way for developing secure, transparent, and efficient supply chain management systems in the face of growing complexity and security risks.

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Security Challenges of Blockchain-Based Supply Chain Systems

Cited by 7 publications

References 27 publications

A Blockchain-Based Fish Supply Chain Framework for Maintaining Fish Quality and Authenticity

A Blockchain-Based Fish Supply Chain Framework for Maintaining Fish Quality and Authenticity

Blockchain-Based Zero Trust Supply Chain Security Integrated with Deep Reinforcement Learning

Blockchain-Based Zero-Trust Supply Chain Security Integrated with Deep Reinforcement Learning for Inventory Optimization

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