# Systematic Analysis of Risks in Industry 5.0 Architecture
## 3 Literature Review
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Ref. Study** & **Risks Identified** & **Assets Affected** & **Risk Mitigation Strategies** & **Challenges** \\ \hline \multirow{3}{*}{[9]} & Trust risk: there are significant risks because of AI and automation, and there is a need to build trust in ecosystems. & ICT (Information and Communications Technology) systems, Data & The deployment of IoT nodes using “Authentication” and “trusted security” as security mechanism when interacting with diverse devices. & Establishing security and trust in ecosystems. \\ \hline \multirow{3}{*}{[32]} & The possibility of cyber-physical vulnerabilities resulting from the integration of cyberspace and physical space in Human-cyber-physical systems (HCFS) raises the possibility of compromised decision-making processes, data data breaches, and system malfunctions. & Cyber-physical systems, data confidentiality, and security limits, and encryption. & To protect data and system integrity, mitigation techniques may involve putting strong cybersecurity insecure in place, sending the collecting and use of personal data in HCFS, and encouraging stakeholders to trust and accept automated decision-making processes. \\ \hline \multirow{3}{*}{[33]} & Smart contracts enhance security in decentralized asset management (DAM), that harvest new new results, as data saved and exchanged on blockchain networks. & Adopt secure coding standards, code audits, and testing for smart contract vulnerabilities, incorporating encryption and and metric structure but for action money private information and prevent malicious activity. & Smart contract transactions are irreversible, making it challenging to identify and correct mistakes or fraudulent and metric structure but for action money private information and prevent malicious activity. \\ \hline \multirow{3}{*}{[34]} & Data privacy risks in healthcare, particularly IoT-based systems, pose a significant challenge in supply chain management, particularly in managing data privacy and integration. & Industry 5.0 utilizes decentralized IOT (Industrial Internet of Things), blockchain middleware, and mass customination to integrate data in smart manufacturing from numerous sources and services. & One of the key challenges faced by the shipping sector is data privacy. \\ \hline \multirow{3}{*}{[35,36]} & Eavesdropping, intercepting or misleading-unauthorized access management of sensitive data & IoT communication channels, network setup & Implement secure communication protocols and encryption & Protecting wireless networks and avoiding “man-in-the-middle\" attacks \\ \hline \multirow{3}{*}{[35]} & Brute force attacks: Constant and repeated efforts to guess passwords or keys & IoT end devices, servers, and applications and account lockout features. & Implement secure password guidelines & Security and usability must be balanced, and access credentials must be managed. \\ \cline{1-1} \cline{2-5}  & Denial of Service: Interruption of processes and potential physical threats & IoT end devices, Industrial Control Systems & Network segmentation and intrusion detection systems implementation & Timely component and configuration vulnerability analysis \\ \hline \multirow{3}{*}{[37]} & Security risks include adversarial AI, the responsibility gap, and the unpredictable nature of industrial AI-based systems. & Industrial AI systems, critical industrial assets & ML (Machine-Learning) algorithms should be improved and tested against adversarial AI. & Costly failures and changes, price of skill, high standards for regulations, legal and regulatory difficulties. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Identified Cybersecurity Risks in Industry 5.0.