Cybersecurity has always been a rapidly evolving field, after all, security needs to try to keep up with hackers, malware, and other threats. Today, the latest evolution in cybersecurity is the use of AI to predict threats.

Today, we’re seeing a wave of next-generation (or next-gen) security tools that use Artificial Intelligence (AI) to identify threats in action. AI, including machine learning and deep learning, is the backbone of next-gen security.

How AI Is Leading the Way

Next-gen security tools use artificial intelligence (AI), machine learning (ML) and deep learning (DL) to identify threats and respond quickly to address them. The beauty of AI, ML, and DL in cybersecurity tools is that they can not just identify a threat after it has breached your network, they can stop it proactively.

The areas in cybersecurity where AI shows the most promise are:

  • Malware Detection
  • Intrusion Detection
  • Fraud Detection
  • Network Risk Scoring
  • User and Machine Behavior Analysis

ai-cybersecurityAI in Endpoint Security

The number of endpoint devices is expected to grow exponentially in the next decade. Endpoint devices include everything from mobile devices to fitness trackers, to industrial sensors and Internet of Things (IoT) devices.

When it comes to securing this new world of connected endpoint devices, the “trust but verify” approach to security no longer works. AI and next-gen security tools, combined with a Zero Trust security model, can help you stay ahead of the hackers. An endpoint detection and response (EDR) tool with AI capabilities can identify advanced threats that anti-malware tools might miss.

Prediction versus Detection

Traditional firewalls use a database of known threats to identify a hack or malware infection as it is happening. This prediction method relies on the knowledge of threats that have already occurred to identify vulnerabilities to those kinds of attacks. 

Now, next-gen cybersecurity tools with AI can use data modeling to detect potential threats. AI, ML and DL can learn from patterns of behavior to separate regular network, user and machine activity from irregular, and therefore suspicious, activity. These tools can also use deep learning to analyze data from widely disparate sources to see the big-picture threat landscape and predict threats as they are forming.


The Future of Cybersecurity is Here

In an ideal world, threats will be identified by what they are attempting to do, not what they are doing. Luckily, the future is here — AI is redefining every aspect of cybersecurity. From better EDR to detecting threats as they’re happening, to firewalls that use deep learning to detect known and unknown malware.

By leveraging the power of AI in cybersecurity and investing in next-gen security tools, you can better protect your network now and tomorrow. To learn more, check out our ebook, The Realities vs. The Hype of Next-Gen Security.