## 5 The Security and Privacy of Edge Computing
[227] proposes an FL-based DT framework called SAINT, designed to address challenges in resource scheduling for 5G edge computing-empowered distribution grids. SAINT optimizes latency, accuracy, and security by reducing iteration delay, enhancing model recognition, and supporting intelligent resource scheduling while considering energy consumption and access priority. Several studies have focused on how blockchain technology can reduce the processing load on the cloud and minimize the latency between IoT devices and the cloud. The integration of blockchain and EC provides a decentralized approach to address security and data integrity issues in IoT networks, providing a reliable authentication and data storage mechanism [228; 229]. Although EC improves the security of sensitive data, it poses security challenges such as authentication of IoT devices and edge servers and risks such as vulnerability to malicious attacks [230]. Accordingly, the hybrid centralized and blockchain-based authentication architecture proposed by [231] provides an efficient and decentralized authentication mechanism for IoT systems using edge computing. While deploying edge servers for centralized authentication, it uses a lightweight blockchain network to increase security, reduce transaction costs, and meet the scalability and real-time performance needs of IoT devices. Blockchain technology strengthens the security of EC with its immutable, hack-resistant, and decentralized data storage features, securing transactions between IoT devices and acting as a trusted database [232]. In addition, blockchain's consensus mechanisms provide an innovative method for distributed database management and new payment models for network services in edge environments. The integration of EC and blockchain combines CC, data processing, and access control in a secure and unified platform, enabling rapid deployment of computational services to edge servers and accelerating the development of the Industrial Internet of Things (IIoT). In this context, a blockchain-enabled edge intelligence framework is proposed to provide secure and flexible edge service management, including cross-domain sharing-based scheduling of edge resources and a credit-based edge transaction approval mechanism. Numerical results show that these approaches provide significant improvements in both edge service cost and capacity [233]. Furthermore, a lightweight secret key agreement protocol based on public key with self-authentication has been developed to enable secure communication in resource-constrained edge devices. These mechanisms work together to provide IIoT security guarantees such as authentication, auditability, and confidentiality [234]. In addition to improving security, deep learning-based user authentication, combined with hybrid encryption, enhances blockchain-aided data storage while optimizing task offloading in MEC. This approach improves data integrity, boosts computational efficiency, and further strengthens security in decentralized environments [235]. The concept of \"decentralizing edge devices\" leverages blockchain technology to establish a distributed ecosystem where edge devices operate independently without reliance on a central authority. Blockchain ensures secure interactions by tracking, verifying, and regulating the behavior of these devices while managing their data exchange. This decentralized structure enables edge devices to support distributed computing platforms, facilitating collaborative execution of computational tasks without a central governing entity [236]. Moreover, blockchain-based decentralization can lead to more adaptable and secure distributed networks, fostering the development of decentralized applications. In this context, a power allocation platform has been proposed, utilizing a decentralized edge computing model to enhance resource efficiency and security [237]. While deep learning-based decentralized authentication and hybrid encryption significantly enhance security and efficiency, their implementation presents notable challenges.