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Solutions Reviews Contributed Content Series is a collection of contributed articles written by thought leaders in enterprise tech. In this feature, Rockwell Automations Albina Ortiz offers commentary on securing data collection and analysis at the edge.

Despite being around since the 1990s, manufacturers have only recently adopted edge computing, driven by the advance of digital transformation and the expansion of Internet of Things (IoT) device connectivity to enterprise networks. This dispersed computing model brings computation and data storage closer to the networks data source or edge (hence the name) rather than relying solely on centralized cloud servers. Its ability to bring storage and computation closer to machines and locations that need it is now proving its worth to C-level executives.

While edge computing offers numerous advantages, it also raises significant security concerns. Securing data collection and analysis at the edge is crucial in todays connected world, especially as more devices and sensors are deployed in remote or distributed environments and may be more vulnerable to physical attacks or unauthorized access. In this article, we will explore why edge computing is both a blessing and a challenge from a cybersecurity perspective, why securing a distributed network requires careful consideration, and how manufacturers can help protect themselves from breaches.

From a cybersecurity perspective, edge computing has many beneficial attributes for enterprises, including improved response time, bandwidth optimization, and decreased security concerns. Lets highlight some of the main benefits:

By moving security applications closer to the data and devices they are protecting, edge computing reduces latency, improving their performance and making it easier to detect and respond to threats in real time. Edge computing also reduces bandwidth utilization and brings data storage and processing closer to the user, delivering quicker response times than cloud computing and improving performance. By processing data closer to where its generated, applications can respond more quickly, making it ideal for real-time and latency-sensitive applications such as IoT devices, autonomous vehicles, high-quality live video streaming, and augmented reality (AR).

Edge computing helps improve the overall security posture by distributing security controls throughout the network, making it more difficult for attackers to gain a foothold and compromise the entire system. In addition, deploying real-time threat detection and response systems using edge computing can identify and block attacks before they reach central data centers. With data no longer being sent over long distances, edge computing aids in security enhancements, shielding sensitive data from potential cyber threats and reducing the risk of data breaches. Edge computing can also authenticate and authorize devices before they are allowed to connect to the network, helping prevent unauthorized devices from accessing sensitive data and systems.

Computing at the edge can help improve data privacy by reducing the amount of data that needs to be transmitted to central data centers and encrypting the data sent, making it more difficult for threat actors to steal or intercept sensitive data. Enhancing data privacy and security through edge computing keeps sensitive data localized, reducing the need to transmit it over public networks. This is crucial for industries like healthcare and finance, which handle sensitive information.

Edge computing can help reduce an organizations attack surface by offloading some processing and storage from central data centers. This can make it more difficult for attackers to find and exploit vulnerabilities.

Zero-trust security models implemented using edge computing further enhance overall security by verifying all users and devices identities and authorization before granting access to resources. This can help prevent attackers from gaining access to sensitive data and systems, even if they have compromised a users account or device.

The flip side of edge computing is that it introduces several security risks that enterprises must consider and address. These risks stem from edge networks distributed nature, edge devices diversity, and the potentially remote and less secure environments where these devices may be deployed. Lets take a close look at these challenges:

The nature of edge computing involves distributing devices and applications to the edge of the network, which can make them more challenging to secure and manage. The diverse range of devices, from simple sensors to powerful servers, can make it difficult to develop and implement effective and adequate security controls for all devices.

Achieving interoperability and maintaining data consistency across distributed edge nodes, devices, and platforms is also a challenge. Ensuring that all nodes have access to the most up-to-date information without introducing conflicts is complex, so making sure that different devices and protocols can work together seamlessly is an ongoing concern.

Edge devices typically have limited computational power, memory, and storage compared to cloud servers. This constraint can make it challenging to run resource-intensive applications, handle large datasets at the edge, and difficult to deploy robust security measures like intrusion detection systems or complex encryption algorithms.

Additionally, edge devices may not receive timely security patches or updates due to their remote locations or constrained resources, so vulnerabilities may persist longer on these devices, making them attractive targets for attackers. Edge devices, especially personal devices, can often be misconfigured, creating additional potential security vulnerabilities.

Often located in remote or unsecured locations, edge devices can be more vulnerable to physical attacks. Edge devices exposed to extreme weather conditions, power fluctuations, or other environmental factors can impact their security and reliability. The increased number of secured devices and data points that edge computing facilitates raises the chance of security breaches. Moreover, weak authentication and authorization mechanisms can allow unauthorized users or devices to access and manipulate data or control edge devices, so proper identity and access management are critical.

Managing a distributed network of edge devices can be more complex than a centralized cloud infrastructure, creating new attack vectors and additional entry points for attackers. Threat actors can exploit those devices vulnerabilities to gain network access or steal data.

Edge computing can include a higher up-front cost for the initial acquisition of additional hardware and software, in addition to potential training required to manage and maintain a new solution, despite the savings over the longer term.

The businesss specific needs must be considered when securing a distributed network. For example, a company that relies on real-time data processing may need to implement stricter security controls to help protect against data breaches and denial-of-service attacks. Securing a distributed network presents a unique set of challenges and vulnerabilities that differ from those of traditional centralized networks and require careful consideration.

Why is this? In short, complexity, the variety of devices with different operating systems and security vulnerabilities, the demand for compliance, and network visibility.

Distributed networks are complex and have no central point of control or authority. They involve several technologies, vendors, locations, and, often, multiple perimeters and consist of various devices, nodes, or endpoints with different operating systems and inherent security vulnerabilities. Remote devices, such as laptops and mobile devices, can be more challenging to secure than devices on-premises. This extensive attack surface provides attackers with more opportunities to exploit weaknesses, and decentralization can make it harder to enforce security policies, monitor network activity, and respond to threats in a coordinated manner. Securing each component and the channels between them is an essential consideration.

The dynamic nature of distributed networks means they are constantly changing, making it difficult to maintain visibility into all aspects of a distributed network, keep up with security risks, and ensure that security controls are adequate. Enterprises need to be conscious of these dynamics when considering security.

Distributed networks often handle sensitive data, and many industries have regulatory requirements (e.g., GDPR, HIPAA) that mandate strict data protection measures. Achieving and maintaining compliance across a distributed network can be complex and demanding. Meeting these regulatory requirements is a crucial consideration for securing a distribution network.

Securing a distributed network effectively and providing protection from security breaches requires a comprehensive security strategy that identifies specific security risks and implements appropriate controls to mitigate those risks. The security strategy requires regular reviews and updates to remain effective. Below are some key elements that form part of a robust cybersecurity strategy for edge computing networks.

A zero-trust security model verifies the identity and authorization of all users and devices before granting access to resources. This can help to prevent attackers from gaining access to sensitive data and systems, even if they have compromised a users account or device.

Strong authentication and authorization mechanisms verify the identity of edge devices and users accessing them. These controls help prevent unauthorized users and devices from accessing sensitive data and systems and can include certificates, keys, or biometric authentication. Using role-based access control (RBAC) to define and manage permissions for devices and users limits access to only what is necessary for each entity.

Implementing security segmentation to isolate different parts of the network and edge devices from critical systems can limit the damage caused by a successful attack and help prevent attackers from moving laterally through the network if they can compromise one device or application. Installing firewalls and intrusion detection systems (IDS) enables monitoring and controlling traffic between segments.

Encrypting data at rest and in transit can help to protect it from being intercepted or stolen. It is crucial to ensure that data is encrypted and transmitted between edge devices and data storage or processing centers using secure protocols like MQTT, CoAP, and AMQP. Encrypting data stored on edge devices, especially with persistent storage, using encryption algorithms and keys that meet industry standards, helping protect data in place.

Developing a robust patch management process to keep edge devices up to date with the latest security patches and firmware to address known vulnerabilities is essential for managing them as they are discovered and making it more difficult for attackers to exploit them. Hardware-based security features such as Trusted Platform Modules (TPMs) can store encryption keys and help ensure the devices integrity.

Implementing data integrity checks, such as hash functions, can ensure that data hasnt been tampered with during transmission or storage while validating data at the edge filters out potentially malicious or erroneous data before analysis. Defining clear data retention and disposal policies at the edge helps ensure that data is not stored longer than necessary to reduce the risk of unauthorized access.

Implementing real-time monitoring of edge devices and networks helps detect and respond to security incidents quickly and effectively. Using intrusion detection systems and anomaly detection can identify suspicious activity while maintaining detailed logs of device and network activities that can be analyzed for security incidents and breaches. Its essential to have a well-defined incident response plan to address security breaches promptly, including procedures for identifying, containing, mitigating, and recovering from security incidents.

Employee awareness of security best practices and the importance of data security is vital to understanding potential threats. It can help users avoid making mistakes that could lead to security breaches. Training employees and personnel working with edge devices and data is essential to an enterprises security strategy.

Staying informed about relevant data privacy and security regulations, such as GDPR, HIPAA, or industry-specific standards, is another crucial element of a security strategy to ensure compliance with these regulations in edge computing environments.

Edge computing offers enterprises many benefits, including increased data processing and speed, reduced latency, improved data privacy, and bandwidth optimization. It also brings unique security challenges that must be addressed to protect sensitive data.

Securing a distributed network is a complex task due to its expansive and diverse nature and the need to address various technical, operational, and compliance challenges. Securing data collection and analysis at the edge is an ongoing process that requires a proactive approach, especially as more devices and sensors are deployed in remote or distributed environments.

To mitigate security risks in edge computing environments, organizations should adopt a comprehensive security strategy that includes strong authentication, encryption, intrusion detection, regular patching, secure device provisioning, and continuous monitoring. Additionally, security best practices should be integrated into the design and deployment of edge solutions to minimize vulnerabilities and safeguard critical assets and data. Collaboration with experts in cybersecurity and regular security audits can also help ensure the effectiveness of security measures.

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Securing Data Collection and Analysis at the Edge - Solutions Review