Many edge devices prioritize functionality and connectivity over security. They are often small and physically exposed, making them vulnerable to theft. And some strategies intended to secure the edge, such as relying on vulnerable VPN connections, can increase the risk of zero-day attacks. Processing data locally using edge devices distribute power across a network and reduces bandwidth requirements at central locations. This can lower costs and improve performance.
AI/Machine Learning
Machine learning is the technology behind artificial intelligence, and it is a subfield of computer science that enables a machine to learn from experience or data without being explicitly programmed. The technology identifies patterns and predicts new data sets, improving computers’ performance. It uses complex algorithms to analyze and understand unstructured information.
A common business application of AI is in customer service, where companies use natural language processing and chatbots to automate responses and offer guidance. It’s also used in marketing to make recommendations for content, and it can help with search optimization, reducing the amount of data that a user needs to input to find what they want.
IT professionals mentioned that the standard edge computing security benefits is detecting and mitigating cyber-attacks. The technology can scan data to look for suspicious activity and identify application vulnerabilities – with some systems even capable of self-healing. Some businesses are using AI to monitor their facilities and employees. Construction companies, utilities, farms, and mining interests utilize AI-enabled software to track worker behavior and ensure workers follow safety protocols. Other organizations are deploying AI to automate fraud detection, minimizing the time it takes to investigate suspected fraud and improving overall accuracy. Some are also using the technology in predictive maintenance, enabling them to predict when equipment will need servicing and optimize the scheduling of maintenance visits.
Zero-Trust Networks
Zero trust is a security model that eliminates implicit trust in the network perimeter and relies on processes, policies, and technologies to authenticate and authorize users, devices, and applications continuously. This is a fundamental shift in how organizations should defend their attack surface, especially as the lines between work and home have blurred with remote work policies and as more employees on various devices access cloud-based apps. It takes a layered approach with identity protection, threat detection, micro-segmentation, and secure access service edge (SASE) tools. These systems provide a strong defense against attacks through a policy of least-privilege access, strict user authentication, and continuous validation that ensures the health of endpoints, cloud workloads, and applications. The best Zero Trust networks combine these technologies to build a strong foundation that prevents attackers from exploiting vulnerable areas of the business. This also helps limit the potential impact of lateral movement within an organization that has been breached.
Detection
As companies move more and more data to the network edge, IT teams need to secure remote access without slowing down productivity. That’s why they are turning to edge security, a subset of cybersecurity that protects data outside traditional corporate networks. Edge security uses many fundamentals as centralized cybersecurity systems but at a smaller scope. For example, a company must ensure that all data at the network edge is encrypted and that connectivity uses multi-factor authentication protocols. The principle of least privilege (POLP) also applies to the network edge, with only the minimal amount of data and functionality granted to users at each device. Using advanced analytics tools, companies can detect anomalies and take action to prevent threats from occurring. They can also use AI/machine learning to monitor the behavior of network devices in real-time and alert personnel when suspicious activity is detected. To keep the network safe, it’s crucial to implement a Zero Trust access model for all devices and users. This approach removes many potential threats from the edge computing environment because it doesn’t rely on predefined trust levels.
Prevention
As edge computing brings massive amounts of data closer to the users, it also opens up new avenues for hackers to breach security. Businesses must adopt and implement new technologies to protect against cyberattacks.
The same security fundamentals in more centralized networks must be applied to secure the edge. That includes making sure the entire network is visible to administrators, that data is encrypted both at rest and in transit, and that automated monitoring systems are in place that can quickly detect any strange behavior. It’s also crucial that physical security measures be taken into account. That means locking down devices, ensuring only authorized workers know their location and that they’re only using approved hardware and software. Using logical safeguards like encryption, RBAC and ABAC access controls, and stringent authentication policies are also key. Many potential customers have asked how to prevent tampering with the data or system and how they can be prevented from breaching if a device is compromised. The answer is that a Zero Trust network is the best way to do that. If a device isn’t on the company’s approved list of edges, it shouldn’t even be able to connect to the company’s infrastructure in the first place.
