## 4 Security Threat Landscape in 5G Networks
### Analysis of 5G Security Challenges in Conjunction with Edge Computing
Additionally, edge computing environments often lack the physical security measures present in traditional data centers, making them susceptible to physical attacks. Compromised hardware could lead to the loss or theft of sensitive data. Moreover, the heterogeneity of edge devices often results in a lack of uniform security protocols and standards. This inconsistency can be exploited by attackers to launch cyberattacks, such as DDoS attacks or malware infection [70]. Implementing robust protective measures in edge computing is critical to secure the operations of 5G networks. The mitigation strategies should take into account the unique challenges of edge computing, including the high number of devices, the decentralized data processing, and the inconsistency of security protocols among devices. Firstly, as edge computing expands the surface area for potential attacks, perimeter defense strategies must be upgraded to be more dynamic and responsive. This includes utilizing machine learning algorithms for threat detection and mitigation, which can adapt and respond to emerging threats in real time [68]. Secondly, the concept of \"security by design\" should be implemented in edge computing environments. This approach involves integrating security measures at every stage of system design and operation, rather than applying them as an afterthought. Moreover, data encryption should be applied to ensure the integrity and confidentiality of data, preventing unauthorized access and manipulation. It is essential to deploy robust encryption mechanisms to secure the communication between edge devices and central nodes. Additionally, the standardization of security protocols across edge devices can enhance their resilience against cyberattacks in edge applications. Establishing industry-wide standards for edge security would help create a more unified and less vulnerable security landscape. Further, a summary of the security challenges in edge computing in 5G, along with potential risks, vulnerabilities, and protective measures, is displayed in Table 8. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Security Challenges in Edge Computing in 5G** & **Potential Risks and Vulnerabilities** & & **Protective Measures** \\ \hline \multirow{4}{*}{Decentralization of data processing processing} & - & Increased attack vectors due to processing data closer to users. Edge nodes with lower computational capacity are more vulnerable. & - & Upgrade perimeter defense strategies to be dynamic and responsive. - & Upgrade perimeter defense strategies to be dynamic and responsive. - & Upgrade perimeter defense strategies to be dynamic and responsive. - & Upgrade perimeter defense strategies to be dynamic and responsive. - & Upgrade perimeter defense strategies to be dynamic and responsive. - & Upgrade perimeter defense strategies to be dynamic and responsive. - & Upgrade perimeter defense strategies to be dynamic and responsive. - \\ \cline{1-1}  & - & Edge nodes with lower computational capacity are more vulnerable. & - & Implement machine learning for real-time threat detection and mitigation. - & Upgrade perimeter defense strategies to be detection and mitigation. - \\ \cline{1-1}  & - & - & Apply ”security by design” principles in system design and operation. & \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Fifth-generation security challenges and edge computing: potential risks, vulnerabilities, and protective measures [68; 69; 70]. Table 8 outlines the security challenges inherent to the integration of edge computing within 5G networks. It identifies key risks such as increased attack vectors due to data decentralization, varied security standards in IoT devices, and data integrity concerns. Each challenge is paired with recommended protective measures like robust encryption, machine learning for threat detection, and industry-wide security standardization.