## 2 Related Work  
The application of emerging technologies, such as blockchain (BC) and deep reinforcement learning, has gained significant attention in the field of supply chain (SC) management to address security challenges and optimize performance. This section reviews the recent literature on BC and DRL approaches for enhancing SC security and efficiency. Blockchain technology has been widely explored for its potential to revolutionize SC management by providing secure, transparent, and tamper-proof record-keeping [2]. [PERSON] et al. [14] conducted a comprehensive survey of BC implementations and use cases for SCs, highlighting the benefits of BC in enhancing traceability, trust, and automation. [PERSON] et al. [15] proposed a trust management framework called TrustChain, which leverages BC and Internet of Things (IoT) technologies to establish trust among SC stakeholders [4]. These studies demonstrate the potential of BC in addressing security challenges and improving transparency in SCs. While the primary focus has been on supply chains, blockchain technology has also found significant applications in other areas requiring robust security and traceability solutions. Healthcare: Blockchain technology has been employed to secure medical data sharing schemes, as discussed by [PERSON] et al. [16], who explore its role in enhancing data privacy and integrity within healthcare systems, an area that parallels the security and confidentiality needs of supply chains. Luxury Goods: In the luxury goods sector, blockchain helps combat counterfeiting, a challenge similar to that faced by supply chains in verifying the authenticity of goods. [PERSON] et al. [17] provide insights into how blockchain-based solutions are being deployed to ensure the authenticity and traceability of luxury products. Pharmaceutical Industry: The pharmaceutical industry has utilized blockchain to ensure drug safety and combat fraudulent activities, which resonates with the supply chain's need for secure and verifiable tracking of product origins and handling. This application is detailed in the literature review by [PERSON] et al. [18], which discusses the successful implementation of blockchain technology in pharmaceuticals. IoT Integration: The integration of blockchain with IoT devices, which is pivotal in managing complex supply chain networks, is explored by [PERSON] et al. [19]. Theydiscuss how this integration faces challenges and opportunities in ensuring secure and efficient operational workflows. Federated Learning: Similarly, the intersection of blockchain with federated learning for enhancing data security in decentralized environments is examined by [PERSON] et al. (20), highlighting its potential to secure data across distributed computing frameworks, much like in supply chain environments. Deep reinforcement learning has emerged as a promising approach for optimizing various aspects of SC management, such as inventory control and network design. [PERSON] and [PERSON] (20) proposed a DRL-based approach for empowering security and trust in 5G and beyond networks, showcasing the potential of DRL in proactive attack detection and mitigation. However, the application of DRL in the context of SC security is still an emerging research area, and further investigations are needed to develop robust and scalable solutions. The integration of BC and DRL has been explored to create secure and efficient SC solutions. [PERSON] et al. (20) reviewed open-source software SC attacks and highlighted the need for proactive and adaptable threat prevention, detection, and response mechanisms. [PERSON] et al. (20) discussed the security challenges of BC-based SC systems and emphasized the importance of implementing robust cybersecurity measures. These studies underscore the necessity of combining BC and DRL to develop comprehensive SC security frameworks. The concept of zero trust has gained traction in the cybersecurity domain, assuming no implicit trust and continuously verifying and validating all entities and transactions.