How is AI benefitting SASE?

Short answer: AI helps SASE by learning how users, devices and applications normally behave, so it can spot anomalies, protect sensitive data, block new variants of known threats in real time and take routine work off security analysts.

SASE is a term that has been on everyone’s mind when you think of security. Since its inception, SASE has been garnering a lot of attention and for mostly the right reasons. There is no denying that SASE is here to stay.

SASE providers collect data on cybersecurity and networking threats, which helps them and their customers prepare for new technologies and threats.

SASE has a few core components rolled up in its sleeve. Them being, SD-WAN, firewall-as-a-service (FWaaS), Secure Web Gateway (SWG) , Cloud Access Security Broker (CASB), Zero Trust Network Access (ZTNA) and a technology that is the most crucial today, which plays a key role in every aspect of SASE, Artificial Intelligence (AI).

Artificial Intelligence being one where most of the SASE vendors have been working on. With all the data the vendors have collected over the years, AI and Machine Learning (ML) has a great potential to produce smarter and faster results.

Today, Artificial Intelligence and automation capabilities are some of the key features that enterprises are looking for when they choose SASE. Here is how AI benefits SASE, and everything you need to know about it.

1. User and entity behavior analytics – SASE helps establish how humans and machines act within a network, which helps in spotting any suspicious activity as well as in authentication. AI models work here in identifying various endpoints that are connected to a network, along with profiling those clients that have access to those networks along with increasing awareness to the security experts.
2. Data loss prevention – Data Loss Prevention, as the name suggests helps preventing sensitive data from leaving the company’s system whether it’s someone on the inside trying to steal sensitive information or external attackers. AI helps with tracking these sensitive information and who has access to them, along with denying access to individuals who may seem suspicious to putting such data to risk.
3. Anomaly detection – A ML algorithm that can detect activity that does not fit normal patterns. AI proves to be beneficial here where it detects behaviors that aren’t good or bad and becomes difficult for traditional networks to detect.
4. Identifying and preventing zero-day attacks – Today, AI models are being trained to know and understand all vulnerabilities and attacks that haven’t happened, but may occur. These can be stopped immediately, as many new attacks are all different variations of previously known threats. AI engines are used to stop malware by pushing ML models, which help stop these in real time.
5. Easing the burden on security analysts – By handling routines tasks with AI, analysts now have the time to focus on other complicated issues. By learning and understanding the tasks of a security professional, AI helps them close their tasks at a much faster pace and with more efficiency.

Along with these, there are many other ways how AI is helping SASE, with reducing false positive, predictive maintenance as well as Network analysis and repair. AI in networking and security is moving quickly: Nexapp’s NexParth AI, for example, answers questions from live fleet data and proposes fixes that wait for approval before they are applied.

Related: SASE vs SD-WAN vs SSE explained, NexParth AI assistant for network operations and Nexapp SSE with ZTNA, SWG, CASB and DLP.

Frequently asked questions

What are the core components of SASE?

SASE combines SD-WAN with security services delivered under one policy: firewall-as-a-service (FWaaS), secure web gateway (SWG), cloud access security broker (CASB) and zero trust network access (ZTNA).

How does AI detect threats in a SASE network?

AI models learn the normal behaviour of users and devices on the network, known as user and entity behaviour analytics. Activity that does not fit those patterns is flagged as a possible threat, including behaviour that traditional rule-based tools would miss.

Can AI stop zero-day attacks?

It can stop many of them. Most new attacks are variations of known threats, so machine learning models trained on known attacks can recognise and block new variants in real time.

How does AI help data loss prevention?

AI tracks where sensitive data sits and who has access to it, and can deny access to users whose behaviour looks suspicious, whether the risk comes from an insider or an outside attacker.

Does Nexapp use AI in its SASE platform?

Yes. NexParth AI answers questions from live fleet data, proposes a fix and waits for approval before acting. It runs on an open-weight model on the customer's own GPU host, so fleet data never leaves the deployment.

Book a demo with Nexapp to find out more about SASE.