2024 certainly proved to be a year of Artificial Intelligence (AI), and it’s likely not going to stop any time soon. The world has been bombarded by marketing buzz around all things AI, from generative Large Language Models (LLMs) to autonomous driving cars, to digital art and animation. We all know that AI and Machine Learning (ML) aren’t new as these technologies have existed for years. More specifically, AI and ML have been a part of networking and security for years and have already driven increased adoption of advanced networking solutions.
SASE (Secure Access Service Edge) incorporates AI by using machine learning algorithms to analyze network traffic patterns, optimize network performance, make intelligent decisions based on real-time data, identify potential threats, and proactively prevent attacks, allowing for a more dynamic and responsive security posture across a distributed network environment.
Some of the ways AI, ML, and automation are used in SASE today:
- Network Optimization:
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- AI can analyze network usage to identify patterns and intelligently route traffic via SD-WAN, optimizing bandwidth allocation, and reducing latency.
- ZTNA:
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- ML can dynamically assess user and device risk to allow or deny access based on real-time information, enabling a more granular level of security.
- Advanced Threat Detection:
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- ML can identify previously unseen malicious traffic patterns, classify malware, and detect anomalies in user behavior to proactively block potential threats.
- Incident Prioritization:
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- By analyzing data from multiple sources, AI can identify the most critical security incidents.
- Automated Response:
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- AI can automatically take actions like blocking malicious IP addresses, isolating compromised devices, or initiating incident response workflows.
SASE solutions are also incorporating some of the more well-known aspects of AI, like LLMs, for generating responses to knowledgebase queries into platform management portals. This allows administrators to ask the platform questions rather than searching through an entire database for the configuration documents needed.
On top of the benefits of using AI, ML, and automation to deliver features and functionality, SASE solutions can also provide value to organizations by protecting data being used to train AI algorithms. CASB and DLP engines provided by SASE platforms can create guardrails around who can access AI applications and what company data can be uploaded. Essentially, AI is used to both deliver a secure network solution and protect AI workloads – AI securing AI.
Overall, AI in SASE can improve the experience for both end users and IT operators by simplifying operations, boosting productivity and efficiency, and potentially reducing costs. Whether you self-manage SASE or work with a managed service provider, AI and ML are already part of the secret sauce for network optimization and security.
If you’re exploring how AI and ML can enhance your network and security strategy, C3 Technology Advisors is here to help. Our team of experts can guide you in evaluating SASE offerings, optimizing your network performance, and ensuring your organization stays ahead of emerging threats. Contact us today to learn how we can help you leverage cutting-edge technology to secure and streamline your operations.
