4 ways AI is changing how IT leaders approach endpoint security

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Security consists of many systems. You have intrusion detection and prevention systems (IDS/IPS). You have security information and event management (SIEM), log management, and data loss prevention (DLP). You have firewall monitoring, firewall log analyzers, and so on.

All of them are collecting data that could help you prevent a breach. But when there’s so much data available to security professionals, it’s tough to make sense of it all, let alone take action.

Collecting data, analyzing data, and determining what it all means can be exasperating – especially if you’re trying to do it manually.

Artificial intelligence (AI) and robotic process automation (RPA) are here to help. They can speed up the process, spot vulnerabilities before they become breaches, and free up time for your security practitioners to address threats more proactively.

Here are four ways AI is changing how IT leaders address endpoint security.

1. Makes sense of massive amounts of data

The process of aggregating all your data into a single repository, dissecting it, and figuring out what everything means can be difficult, inefficient, and most importantly, time consuming. Not with AI.

Instead of having your employees perform predictive analysis, proactive threat monitoring, and threat hunting manually, you could use AI models and RPA to streamline the data collection process.

From there, you can break the data down faster and create easily digestible visualizations that enable better decision-making.

2. Accelerates vulnerability assessment and management

RPA and AI can kick off a vulnerability assessment and develop a report based on the AI model’s analysis.

Based on a simulated pen test or simulated vulnerability assessment, RPA can work in concert with AI to gather evidence of vulnerabilities, parse and scrape the data, then bring it into the AI model, which reads the data and analyzes it. This not only accelerates the process and allows you to identify threats faster but it frees up resources to address the threats you’re most vulnerable to.

In addition, you can use AI and RPA to create a model that predicts how a vulnerability is going to behave. Using data from your SIEM tool, AI can examine what malware or endpoint security issues may have been detected. Based on that data, RPA can put security controls or countermeasures in place.

Security professionals are even able to use AI to analyze malware’s patterns and behaviors, and predict how it would impact your endpoints. You can use this information to deploy a more accurate countermeasure without the false positives you can get from non-AI solutions.

3. Enhances data loss prevention

AI can step in to protect your organization’s sensitive data by knowing and recognizing what information should be secured.

Using vector machine learning (ML), you can understand, identify, and make sense of certain patterns in your financial data, for example. By learning the data patterns of your organization’s financials, it can strip that information – or encrypt it – if someone accidentally sends the data to unauthorized personnel or a malicious attacker tries to access it.

4. Better secures the development process

Security should be part of development from the start. Most organizations are starting to get this. But it’s still not top of mind during the process. AI helps with that.

AI can work within the agile development process, sifting through the code being developed and running it against the latest security threats and trends to spot any potential flaws or vulnerabilities. If there’s a strong probability the code may have flaws, the AI will alert the developers to fix any vulnerabilities at every phase of development. Using AI and RPA helps developers proactively identify issues before they become problems.

Getting started with AI and RPA

You don’t have to spend countless hours manually monitoring logs, parsing through these logs, and writing policies anymore.

Start by creating an automation center of excellence that identifies ways AI could benefit your company. Identify and define the goals and objectives you want to get out of AI, and create a governance model that ensures the AI will function as intended. When you’re ready to deploy AI and RPA, start incrementally, with a subset of endpoints and users. Train the AI model on the behavior patterns of those users and build it out over time.

AI is offering organizations new advantages in their security practice that free up time, accelerate threat response, and identify vulnerabilities before they become problems. And it’s only going to get better from here.

If you have any questions about using AI to protect your organization, contact your SHI account executive.