Use Cases of Artificial Intelligence in Cybersecurity

use cases of artificial intelligence in cybersecurity

Using AI to make security better

AI is the best way to solve some of our hardest problems, and cybersecurity is definitely one of them. With constantly changing cyberattacks and more devices being made, machine learning and AI can be used to “keep up with the bad guys” by automating threat detection and making it easier to respond than software-driven methods. To understand how to employ artificial intelligence in cyber security, upgrade yourself by joining Artificial Intelligence Course in Chennai.

At the same time, cybersecurity has some challenges that aren’t found elsewhere:

  • A large area to attack
  • Thousands or tens of thousands of devices per company
  • Hundreds of ways to attack
  • There are not enough security professionals with the right skills.
  • Large amounts of data that are no longer a human-sized problem

Many of these problems should be solved by an AI-based cybersecurity posture management system that can learn independently.

Some technologies can be used to teach a self-learning system how to gather data continuously and on its own from all of your enterprise information systems. Then, this data is analyzed and used to find patterns across millions or billions of signals that are important to the enterprise attack surface.

As a result, new levels of artificial intelligence in cyber security are being fed to human teams in many areas, such as:

IT Asset Inventory is the process of making a full and accurate list of all devices, users, and programmes with access to information systems.

Categorization and measuring how important something is to the business are also big parts of inventory.

Threat Exposure: Just like everyone else, hackers follow trends, so what’s cool with hackers changes all the time. AI-based cybersecurity systems can keep you updated on global and industry-specific threats. This can help you make important prioritization decisions based on what is likely to attack your business, not just what could be used.

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Controls’ effectiveness: To keep a strong security posture, it’s important to know how the different security tools and security processes you’ve implemented work. AI can help you figure out where your information security programme is strong and where it needs improvement.

Breach Risk Prediction: AI-based systems can predict how and where you are most likely to be breached based on your IT asset inventory, threat exposure, and the effectiveness of your controls. This way, you can plan to put resources and tools where you are most vulnerable.

Prescriptive insights from AI analysis can help you set up and improve controls and processes to make your organization’s cyber resilience as strong as possible.

Incident response: AI-powered systems can give better context for prioritizing and responding to security alerts, responding quickly to incidents, and finding the root causes of problems so that they can be fixed and similar problems don’t happen again.

Explainability: Recommendations and analyses need to be easy to understand for AI to be used to help human information security teams. This is important to get buy-in from stakeholders across the organization, to understand the effects of different infosec programmes, and to report relevant information to all stakeholders, including end users, the CIO, the CEO, and the board of directors.

Wrapping Up

Today we discussed artificial intelligence in cyber security use cases. This information is helpful for individuals who are working in cybersecurity. To gather more information on AI technology. Get into FITA Academy, which provides top-notch Artificial Intelligence Course In Bangalore.