Edge Security Architecture: Comprehensive Guide to Securing Distributed Computing Infrastructure

August 13, 2025 | Reading Time: 13 minutes 37 seconds

Master edge security architecture with this comprehensive guide designed for network engineers and security professionals. From fundamental concepts to advanced security strategies, this detailed technical guide provides the knowledge and methodologies needed to secure edge computing environments in modern distributed infrastructure.

Introduction: The Critical Importance of Edge Security Architecture

Edge security architecture represents one of the most challenging and critical aspects of modern distributed computing infrastructure. As organizations increasingly deploy computing resources closer to data sources and end users, the traditional security perimeter has dissolved, creating new attack surfaces and security challenges that require innovative approaches and comprehensive understanding. This guide provides network engineers with essential knowledge for designing, implementing, and maintaining robust security architectures at the network edge.

The proliferation of Internet of Things (IoT) devices, mobile computing, and real-time applications has fundamentally transformed how organizations approach network security. Edge computing brings processing power closer to data sources, reducing latency and improving performance, but it also introduces unique security challenges that traditional data center security models cannot adequately address. Edge environments often operate in remote locations with limited physical security, intermittent network connectivity, and minimal on-site technical expertise, making them particularly vulnerable to both physical and cyber attacks.

Understanding edge security architecture is essential for network engineers because edge deployments are becoming ubiquitous across industries. From manufacturing facilities with industrial IoT sensors to retail locations with point-of-sale systems, from healthcare environments with connected medical devices to smart city infrastructure with distributed sensors, edge computing is transforming how organizations process and analyze data. Each of these environments presents unique security challenges that require specialized knowledge and carefully designed security architectures.

Understanding Edge Computing and Network Edge Fundamentals

Defining the Network Edge

The network edge represents the connection or interface between a device or local network and the internet, serving as the entry point to broader network infrastructure. Unlike traditional centralized computing models where processing occurs in protected data centers, edge computing distributes computational resources to locations closer to data sources and end users. This fundamental shift in computing architecture creates new security boundaries that network administrators must understand and protect.

The network edge encompasses various components including routers, switches, firewalls, integrated access devices, and the endpoints they serve. These components form the first line of defense between internal networks and external threats, making edge security architecture critical for overall network protection. The edge serves as both a gateway for legitimate traffic and a potential entry point for malicious actors, requiring careful balance between accessibility and security.

Edge environments differ significantly from traditional data center environments in several key aspects. Physical security is often limited or non-existent, with devices deployed in remote locations that may be accessible to unauthorized individuals. Network connectivity may be intermittent or limited, making it difficult to maintain consistent security updates and monitoring. Local technical expertise is frequently unavailable, requiring security solutions that can operate autonomously with minimal human intervention.

Edge Computing vs Traditional Computing Models

Edge computing fundamentally differs from traditional centralized computing models in its distributed nature and proximity to data sources. While traditional computing relies on powerful centralized servers in protected data centers, edge computing distributes processing power across numerous smaller devices located closer to where data is generated and consumed. This distribution provides significant benefits including reduced latency, improved bandwidth utilization, and enhanced reliability, but it also creates new security challenges.

The security implications of this distributed model are profound. Instead of protecting a single, well-defined perimeter around a data center, organizations must now secure hundreds or thousands of edge locations, each with its own unique characteristics and vulnerabilities. This multiplication of attack surfaces requires new approaches to security architecture that can scale effectively while maintaining consistent protection across diverse environments.

Traditional security models relied heavily on network perimeters, with strong defenses at the boundary between internal and external networks. Edge computing environments cannot rely solely on perimeter defenses because the perimeter itself is distributed and often poorly defined. This reality has driven the adoption of zero-trust security models that assume no inherent trust in any network location or device, requiring verification and validation for every access request regardless of its origin.

Core Edge Security Architecture Principles

Zero Trust Security Model

Zero trust security represents the foundational principle for effective edge security architecture. Unlike traditional security models that assume internal networks are trustworthy, zero trust assumes that threats can exist anywhere and that no device, user, or network location should be inherently trusted. This principle is particularly relevant for edge environments where devices operate in potentially hostile physical environments with limited oversight.

Implementing zero trust in edge environments requires several key components. Identity verification must occur for every access request, regardless of the requesting device's location or previous authentication status. Network segmentation must isolate edge devices and limit their ability to communicate with other network resources unless specifically authorized. Continuous monitoring must track device behavior and network traffic to identify potential security incidents in real time.

The zero trust model addresses many of the unique challenges of edge security by eliminating assumptions about network trustworthiness. Edge devices are treated as potentially compromised from the moment they are deployed, requiring ongoing verification of their identity and behavior. This approach provides robust protection even when edge devices operate in unsecured physical environments or experience network connectivity issues that might prevent traditional security updates.

Defense in Depth Strategy

Defense in depth provides multiple layers of security controls to protect edge environments from various types of attacks. This strategy recognizes that no single security control is perfect and that attackers may successfully bypass individual defenses. By implementing multiple overlapping security layers, organizations can ensure that the failure of any single control does not result in complete system compromise.

Physical security forms the first layer of defense in edge environments, though it is often the most challenging to implement effectively. Edge devices may be deployed in remote locations where traditional physical security measures are impractical or impossible. Organizations must consider tamper-evident enclosures, secure mounting systems, and environmental monitoring to detect unauthorized physical access attempts.

Network security provides the next layer of defense, including firewalls, intrusion detection systems, and network segmentation. Edge environments require careful network design to ensure that compromised devices cannot access critical network resources or spread attacks to other systems. Virtual private networks (VPNs) and encrypted communication channels help protect data in transit between edge devices and central systems.

Application and data security represent the innermost layers of defense, protecting the actual information and processes that edge devices handle. This includes encryption of sensitive data, secure coding practices for edge applications, and access controls that limit what actions edge devices can perform. Regular security updates and patch management ensure that known vulnerabilities are addressed promptly.

Secure by Design Principles

Secure by design principles ensure that security considerations are integrated into edge systems from the initial design phase rather than added as an afterthought. This approach is particularly important for edge environments where retrofitting security controls may be difficult or impossible due to resource constraints or physical accessibility limitations.

Security requirements must be defined early in the design process, considering the specific threats and vulnerabilities that edge environments face. This includes understanding the physical environment where devices will be deployed, the types of data they will handle, and the network connectivity they will have. These requirements drive architectural decisions about hardware selection, software design, and security control implementation.

Threat modeling provides a systematic approach to identifying potential security risks and designing appropriate countermeasures. For edge environments, threat models must consider both traditional cyber threats and physical threats that may not be relevant in data center environments. This includes threats such as device theft, physical tampering, environmental attacks, and supply chain compromises.

Edge Security Threats and Vulnerabilities

Physical Security Challenges

Physical security represents one of the most significant challenges in edge security architecture due to the distributed and often remote nature of edge deployments. Unlike data center environments where physical access is strictly controlled, edge devices are frequently deployed in locations where unauthorized physical access is possible or even likely. This exposure creates unique vulnerabilities that must be addressed through both technical and procedural controls.

Device theft represents a primary physical threat to edge environments. Edge devices often contain sensitive data, cryptographic keys, or configuration information that could be valuable to attackers. When devices are stolen, organizations face not only the direct cost of replacement but also the potential for data breaches and unauthorized network access. Secure device design must consider how to protect sensitive information even when devices fall into unauthorized hands.

Physical tampering attacks attempt to modify edge devices to bypass security controls or extract sensitive information. These attacks may involve sophisticated techniques such as hardware implants, firmware modifications, or side-channel attacks that monitor electromagnetic emissions or power consumption patterns. Protecting against tampering requires tamper-evident hardware designs, secure boot processes, and hardware security modules that can detect and respond to physical intrusion attempts.

Environmental attacks exploit the physical conditions where edge devices operate. This may include extreme temperatures, humidity, vibration, or electromagnetic interference designed to cause device malfunctions or security failures. Edge devices must be designed to operate reliably in challenging environmental conditions while maintaining their security properties.

Network-Based Attacks

Network-based attacks against edge environments exploit the distributed nature of edge computing and the often-limited network security controls available at edge locations. These attacks may target the communication channels between edge devices and central systems, attempt to compromise edge devices through network-based exploits, or use compromised edge devices as launching points for attacks against other network resources.

Man-in-the-middle attacks attempt to intercept and potentially modify communications between edge devices and central systems. Edge environments are particularly vulnerable to these attacks because network infrastructure at edge locations may be less secure than in data center environments. Attackers may compromise network equipment, establish rogue access points, or use other techniques to position themselves in the communication path.

Distributed denial of service (DDoS) attacks can target either edge devices themselves or use compromised edge devices to attack other targets. Edge devices with limited processing power and network bandwidth may be particularly vulnerable to DDoS attacks that could disrupt their normal operations. Conversely, large numbers of compromised edge devices can be used to generate significant attack traffic against other targets.

Network reconnaissance attacks attempt to map edge network infrastructure and identify potential vulnerabilities. Attackers may use techniques such as port scanning, service enumeration, and traffic analysis to understand edge network topology and identify potential attack vectors. Edge networks must be designed to limit the information available to potential attackers while maintaining necessary functionality.

Application and Data Vulnerabilities

Application and data vulnerabilities in edge environments stem from the unique constraints and requirements of edge computing. Edge applications often operate with limited computational resources, intermittent network connectivity, and minimal local storage, creating challenges for implementing traditional security controls. These constraints can lead to security compromises that create vulnerabilities for attackers to exploit.

Insecure data storage represents a significant vulnerability in edge environments where devices may have limited encryption capabilities or where encryption keys must be stored locally. Edge devices often process sensitive data that must be protected both in transit and at rest, but the resource constraints of edge environments may limit the cryptographic protections that can be implemented effectively.

Insufficient access controls may result from the need to balance security with operational requirements in edge environments. Edge devices often need to operate autonomously with minimal human intervention, which may lead to overly permissive access controls that allow unauthorized actions. Designing appropriate access controls for edge environments requires careful consideration of operational requirements and security risks.

Insecure communication protocols may be used in edge environments due to legacy system requirements or resource constraints. Many industrial and IoT protocols were designed for closed networks and lack adequate security features for internet-connected environments. Securing these communications often requires additional security layers such as VPNs or application-level encryption.

Essential Edge Security Technologies

Network Segmentation and Microsegmentation

Network segmentation provides fundamental protection for edge environments by isolating different network zones and limiting the potential impact of security breaches. Traditional network segmentation uses VLANs, subnets, and firewalls to create security boundaries, while microsegmentation extends this concept to provide more granular control over network communications at the individual device or application level.

In edge environments, network segmentation must address the unique challenges of distributed infrastructure and limited local security expertise. Segmentation strategies must be designed to operate effectively with intermittent network connectivity and to provide protection even when edge devices cannot communicate with central security management systems. This often requires implementing segmentation controls directly on edge devices or in local network infrastructure.

Microsegmentation provides enhanced security by creating individual security zones for each edge device or application. This approach limits the ability of attackers to move laterally through the network after compromising a single device. Implementing microsegmentation in edge environments requires careful consideration of network performance impacts and the management overhead of maintaining granular security policies across distributed infrastructure.

Software-defined networking (SDN) technologies can simplify the implementation and management of network segmentation in edge environments. SDN allows centralized definition of network policies that can be automatically deployed and enforced across distributed edge infrastructure. This approach provides consistent security controls while reducing the management burden on local personnel who may lack specialized security expertise.

Encryption and Key Management

Encryption provides essential protection for data in edge environments, both for data at rest on edge devices and for data in transit between edge devices and central systems. However, implementing encryption in edge environments presents unique challenges related to key management, performance constraints, and the need to maintain security even when devices operate offline or with limited connectivity.

Data at rest encryption protects sensitive information stored on edge devices from unauthorized access, even if devices are physically compromised. Edge devices often store configuration data, cryptographic keys, and processed information that must be protected from unauthorized access. Implementing effective data at rest encryption requires careful consideration of key storage and management, particularly in environments where hardware security modules may not be available.

Data in transit encryption protects communications between edge devices and central systems from interception and modification. This protection is particularly important in edge environments where network infrastructure may be less secure than in traditional data center environments. Transport Layer Security (TLS) and Virtual Private Network (VPN) technologies provide standard approaches for protecting data in transit, but their implementation must consider the resource constraints and connectivity limitations of edge environments.

Key management represents one of the most challenging aspects of edge encryption implementations. Edge devices must have access to cryptographic keys for encryption and authentication, but storing keys securely on resource-constrained devices in potentially hostile physical environments is difficult. Key management solutions for edge environments must balance security requirements with operational constraints such as device provisioning, key rotation, and recovery from key compromise.

Identity and Access Management

Identity and access management (IAM) in edge environments must address the unique challenges of distributed infrastructure, limited connectivity, and diverse device types. Traditional IAM solutions designed for data center environments may not be suitable for edge deployments due to their reliance on constant network connectivity and centralized authentication services.

Device identity management ensures that only authorized devices can access network resources and that device communications can be authenticated and authorized. Edge environments often include diverse device types with varying capabilities for implementing standard authentication protocols. Device identity solutions must accommodate this diversity while providing consistent security controls across the entire edge infrastructure.

User access management in edge environments must consider scenarios where users may need to access edge resources directly, either for maintenance purposes or for normal business operations. This access must be carefully controlled and monitored to prevent unauthorized actions while enabling necessary operational activities. Role-based access control (RBAC) and attribute-based access control (ABAC) provide frameworks for implementing granular access controls that can adapt to the diverse requirements of edge environments.

Certificate management provides a foundation for device and user authentication in edge environments. Public key infrastructure (PKI) enables the issuance, distribution, and management of digital certificates that can authenticate devices and users even when network connectivity to central authentication services is limited. However, implementing PKI in edge environments requires careful consideration of certificate lifecycle management, including issuance, renewal, and revocation processes.

Implementation Strategies and Best Practices

Risk Assessment and Threat Modeling

Effective edge security architecture begins with comprehensive risk assessment and threat modeling that considers the unique characteristics and challenges of edge environments. This process must evaluate both traditional cybersecurity threats and the physical security risks that are particularly relevant to edge deployments. The distributed nature of edge infrastructure requires a systematic approach to identifying and prioritizing security risks across diverse deployment scenarios.

Risk assessment for edge environments must consider the specific business context and operational requirements of each deployment. Manufacturing environments face different threats than retail locations, and healthcare facilities have different regulatory requirements than smart city infrastructure. The risk assessment process must evaluate the potential impact of various threat scenarios and the likelihood of their occurrence in the specific edge environment being assessed.

Threat modeling provides a structured approach to identifying potential attack vectors and designing appropriate countermeasures. For edge environments, threat models must consider the entire attack surface, including physical access to devices, network communications, and the supply chain through which devices are procured and deployed. This comprehensive approach ensures that security controls address the full range of potential threats rather than focusing only on traditional network-based attacks.

The dynamic nature of edge environments requires ongoing risk assessment and threat modeling as new devices are deployed, network configurations change, and new threats emerge. Organizations must establish processes for regularly reviewing and updating their risk assessments to ensure that security controls remain effective as edge deployments evolve and expand.

Security Architecture Design Patterns

Security architecture design patterns provide proven approaches for implementing security controls in edge environments. These patterns address common security challenges and provide reusable solutions that can be adapted to specific deployment requirements. Understanding and applying appropriate design patterns can significantly improve the effectiveness and efficiency of edge security implementations.

The secure gateway pattern implements security controls at the network boundary between edge environments and central systems. This pattern concentrates security functions such as firewall filtering, intrusion detection, and VPN termination at a single point, simplifying security management and providing consistent protection across multiple edge devices. However, this pattern requires careful consideration of single points of failure and the need for redundancy in critical deployments.

The distributed security pattern implements security controls directly on edge devices rather than relying on centralized security infrastructure. This pattern provides protection even when network connectivity to central systems is limited or unavailable, but it requires more sophisticated edge devices and more complex security management processes. The distributed security pattern is particularly appropriate for edge environments with unreliable network connectivity or strict latency requirements.

The hybrid security pattern combines elements of both centralized and distributed security approaches, implementing some security controls locally on edge devices while relying on centralized systems for other security functions. This pattern provides flexibility to optimize security controls based on specific requirements and constraints, but it requires careful coordination between local and centralized security components.

Monitoring and Incident Response

Effective monitoring and incident response capabilities are essential for maintaining security in edge environments, but they must be adapted to address the unique challenges of distributed infrastructure and limited local expertise. Traditional security monitoring approaches that rely on centralized log collection and analysis may not be suitable for edge environments with intermittent connectivity or limited bandwidth.

Edge monitoring solutions must be designed to operate effectively with limited network connectivity and to provide meaningful security insights even when communication with central monitoring systems is disrupted. This may require implementing local monitoring capabilities on edge devices or in local network infrastructure, with periodic synchronization to central systems when connectivity is available.

Automated incident response capabilities are particularly important in edge environments where human security expertise may not be readily available. Edge security systems must be capable of detecting and responding to security incidents automatically, implementing containment measures to limit the impact of security breaches while alerting central security teams for further investigation and remediation.

The distributed nature of edge infrastructure requires incident response procedures that can coordinate activities across multiple locations and systems. Incident response plans must consider scenarios where edge locations may be isolated from central systems and must be capable of operating independently while maintaining coordination with overall organizational incident response processes.

Regulatory Compliance and Standards

Industry Standards and Frameworks

Edge security architecture must comply with various industry standards and frameworks that provide guidance for implementing effective security controls. These standards address different aspects of edge security, from technical implementation details to governance and risk management processes. Understanding and applying relevant standards is essential for ensuring that edge security implementations meet industry best practices and regulatory requirements.

The NIST Cybersecurity Framework provides a comprehensive approach to cybersecurity risk management that can be applied to edge environments. The framework's five core functions—Identify, Protect, Detect, Respond, and Recover—provide a structured approach to developing edge security programs. However, applying the framework to edge environments requires careful consideration of the unique challenges and constraints of distributed infrastructure.

ISO 27001 provides an international standard for information security management systems that can guide the development of edge security governance processes. The standard's risk-based approach is particularly relevant for edge environments where security risks may vary significantly across different deployment locations and scenarios. Implementing ISO 27001 in edge environments requires adapting the standard's requirements to address the distributed nature of edge infrastructure.

Industry-specific standards may apply to edge deployments in particular sectors. For example, the Industrial Internet Consortium (IIC) has developed security frameworks specifically for industrial IoT and edge computing environments. Healthcare organizations must consider HIPAA requirements when deploying edge systems that handle protected health information. Financial services organizations must comply with regulations such as PCI DSS when edge systems process payment card data.

Compliance Considerations

Compliance with regulatory requirements presents unique challenges in edge environments due to the distributed nature of edge infrastructure and the potential for edge devices to operate across multiple jurisdictions with different regulatory requirements. Organizations must carefully consider how regulatory compliance requirements apply to their edge deployments and implement appropriate controls to ensure ongoing compliance.

Data protection regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) may apply to edge systems that process personal data. These regulations impose requirements for data protection, user consent, and breach notification that must be implemented in edge environments. The distributed nature of edge infrastructure may complicate compliance efforts, particularly for organizations that operate across multiple jurisdictions with different regulatory requirements.

Industry-specific regulations may impose additional requirements on edge deployments. Healthcare organizations must ensure that edge systems comply with HIPAA requirements for protecting patient data. Financial services organizations must implement appropriate controls to comply with regulations such as the Gramm-Leach-Bliley Act and PCI DSS. Critical infrastructure organizations may be subject to sector-specific cybersecurity regulations that impose additional requirements on edge systems.

Audit and compliance monitoring in edge environments requires careful consideration of how to collect and analyze compliance evidence across distributed infrastructure. Traditional compliance monitoring approaches that rely on centralized log collection and analysis may not be suitable for edge environments with limited connectivity or bandwidth. Organizations must develop compliance monitoring strategies that can operate effectively in edge environments while providing the evidence needed to demonstrate regulatory compliance.

Future Trends and Emerging Technologies

Artificial Intelligence and Machine Learning in Edge Security

Artificial intelligence and machine learning technologies are increasingly being applied to edge security challenges, providing new capabilities for threat detection, automated response, and security optimization. These technologies are particularly valuable in edge environments where human security expertise may be limited and where the scale of edge deployments makes manual security management impractical.

AI-powered threat detection systems can analyze network traffic, device behavior, and other security-relevant data to identify potential security incidents in real time. These systems can operate locally on edge devices or in edge infrastructure, providing security monitoring capabilities even when connectivity to central security systems is limited. Machine learning algorithms can adapt to the specific characteristics of each edge environment, improving detection accuracy and reducing false positives over time.

Automated security response capabilities powered by AI can implement containment and remediation actions without requiring human intervention. This capability is particularly valuable in edge environments where security incidents may need to be addressed quickly to prevent their spread to other systems. AI-powered response systems can isolate compromised devices, block malicious network traffic, and implement other protective measures while alerting human security teams for further investigation.

Predictive security analytics use machine learning to identify potential security risks before they result in actual security incidents. These systems can analyze patterns in device behavior, network traffic, and other security-relevant data to predict when security incidents are likely to occur. This predictive capability enables proactive security measures that can prevent security incidents rather than simply responding to them after they occur.

Quantum Computing Implications

Quantum computing represents both an opportunity and a threat for edge security architecture. While practical quantum computers capable of breaking current cryptographic algorithms are still years away, organizations must begin preparing for the quantum computing era by understanding its implications for edge security and beginning the transition to quantum-resistant cryptographic algorithms.

Current cryptographic algorithms that provide the foundation for edge security, including RSA, elliptic curve cryptography, and current symmetric encryption algorithms, will be vulnerable to attack by sufficiently powerful quantum computers. This vulnerability has significant implications for edge environments where cryptographic keys may be stored on devices for extended periods and where updating cryptographic algorithms may be challenging due to resource constraints or limited connectivity.

Post-quantum cryptography research is developing new cryptographic algorithms that will be resistant to quantum computer attacks. However, these new algorithms often have different performance characteristics than current algorithms, potentially requiring more computational resources or producing larger cryptographic outputs. Edge environments with limited computational and storage resources may face particular challenges in implementing post-quantum cryptographic algorithms.

The transition to quantum-resistant cryptography in edge environments will require careful planning and coordination to ensure that security is maintained throughout the transition process. Organizations must develop migration strategies that consider the unique constraints and requirements of edge deployments, including the potential need to update or replace edge devices that cannot support new cryptographic algorithms.

5G and Beyond: Next-Generation Connectivity

Next-generation wireless technologies, particularly 5G and future 6G networks, will significantly impact edge security architecture by enabling new types of edge deployments and changing the threat landscape for edge environments. These technologies provide higher bandwidth, lower latency, and support for massive numbers of connected devices, enabling new edge computing applications while also creating new security challenges.

5G network slicing capabilities allow network operators to create isolated virtual networks with specific performance and security characteristics. This capability can be used to provide dedicated, secure connectivity for edge deployments, potentially simplifying edge security architecture by providing network-level isolation and security controls. However, network slicing also introduces new complexity and potential security vulnerabilities that must be carefully managed.

The increased bandwidth and reduced latency of 5G networks enable new types of edge applications that require real-time processing and response capabilities. These applications may have stringent security requirements that must be met while maintaining the performance characteristics that make them viable. Balancing security and performance requirements in these high-performance edge applications will require innovative security architecture approaches.

The massive scale of device connectivity enabled by 5G networks will significantly increase the number of edge devices that organizations must secure and manage. Traditional security management approaches that rely on manual configuration and monitoring will not scale to support millions of connected edge devices. Organizations must develop automated security management capabilities that can scale to support the massive device connectivity enabled by next-generation wireless technologies.

Conclusion: Building Resilient Edge Security Architecture

Edge security architecture represents a fundamental shift from traditional perimeter-based security models to distributed, zero-trust approaches that can protect computing resources deployed in diverse and potentially hostile environments. The principles, technologies, and strategies outlined in this guide provide the foundation for building resilient edge security architectures that can adapt to evolving threats while supporting the operational requirements of modern distributed computing environments.

The success of edge security implementations depends on understanding the unique challenges and constraints of edge environments and designing security controls that can operate effectively within these constraints. This requires moving beyond traditional security approaches and embracing new technologies and methodologies that are specifically designed for distributed, resource-constrained environments.

As edge computing continues to evolve and expand, security professionals must stay informed about emerging threats, new technologies, and evolving best practices. The edge security landscape is dynamic and rapidly changing, requiring ongoing learning and adaptation to maintain effective security postures. Organizations that invest in building comprehensive edge security capabilities will be better positioned to realize the benefits of edge computing while managing its associated risks.

The future of edge security will be shaped by emerging technologies such as artificial intelligence, quantum computing, and next-generation wireless networks. Security professionals must begin preparing for these technological shifts now, developing the knowledge and capabilities needed to secure edge environments in an increasingly complex and dynamic threat landscape. By building on the foundational principles and practices outlined in this guide, organizations can develop edge security architectures that provide robust protection while enabling the innovation and agility that edge computing makes possible.

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