Preventing Cyberattacks with Artificial Intelligence Versus Traditional Antivirus

What is Artificial Intelligence?

The field of Artificial Intelligence (AI) encompasses a broad range of technologies intended to endow computers with human-like capabilities for learning, reasoning, and drawing useful insights.
In recent years, most of the fruitful research and advancements have come from the sub-discipline of AI named Machine Learning (ML), which focuses on teaching machines to learn by applying algorithms to data. Often, the terms AI and ML are used interchangeably.

Can Machine Learning Keep Me Secure?

Not all problems in AI are candidates for a machine learning solution. The problem must be one that can be solved with data; a sufficient quantity of relevant data must exist and be acquirable; and systems with sufficient computing power must be available to perform the necessary processing within a reasonable time-frame.

What is the Future of AI in Cybersecurity?

As ML proliferates across the security landscape, it’s already raising the bar for attackers. It’s getting harder to penetrate systems today than it was even a few years ago. In response, attackers are likely to adopt ML techniques in order to find new ways through. In turn, security professionals will have to utilize ML defensively to protect network and information assets.

AI Today

Enterprise systems are constantly being updated,modified, and extended to serve new users and new business functions. In such a fluid environment,it’s helpful to have ML-enabled “agents” that can cut through the noise and point you to anomalies or other indicators that provide forensic value.

The Future of AI

Enterprise systems are constantly being updated,modified, and extended to serve new users and new business functions. In such a fluid environment,it’s helpful to have ML-enabled “agents” that can cut through the noise and point you to anomalies or other indicators that provide forensic value.

01

What is Artificial
Intelligence?

The field of Artificial Intelligence (AI) encompasses a broad range of technologies intended to endow computers with human-like capabilities for learning, reasoning, and drawing useful insights.

In recent years, most of the fruitful research and advancements have come from the sub-discipline of AI named Machine Learning (ML), which focuses on teaching machines to learn by applying algorithms to data. Often, the terms AI and ML are used interchangeably.

02

Can Machine Learning
Keep Me Secure?

Not all problems in AI are candidates for a machine learning solution. The problem must be one that can be solved with data; a sufficient quantity of relevant data must exist and be acquirable; and systems with sufficient computing power must be available to perform the necessary processing within a reasonable time-frame.

03

What is the Future
of AI in Cybersecurity?

As ML proliferates across the security landscape, it’s already raising the bar for attackers. It’s getting harder to penetrate systems today than it was even a few years ago. In response, attackers are likely to adopt ML techniques in order to find new ways through. In turn, security professionals will have to utilize ML defensively to protect network and information assets.

AI Today

Learn More

AI Today

Enterprise systems are constantly being updated, modified, and extended to serve new users and new business functions. In such a fluid environment, it’s helpful to have ML-enabled “agents” that can cut through the noise and point you to anomalies or other indicators that provide forensic value.

The Future of AI

Learn More

The Future of AI

As ML proliferates across the security landscape, it’s already raising the bar for attackers. It’s getting harder to penetrate systems today than it was even a few years ago. In response, attackers are likely to adopt ML techniques in order to find new ways through. In turn, security professionals will have to utilize ML defensively to protect network and information assets.

Introduction to Artificial Intelligence for Security Professionals (eBook)

The Cylance Data Team’s recently released eBook covers:

  • Techniques for dividing samples into clusters based on similarities in features and attributes
  • Computational methods for predicting the likelihood that a sample belongs to a predefined class
  • How to use probability as a predictive modeling technique, and how two types of neural networks can be applied to a classification problem
Get Your Copy

More AI Resources
from Cylance

Not All Machine Learning is Created Equal Download White PaperDownload White Paper
AI’s Unique Ability to Stop Tomorrow’s Threats, Today Read BlogRead Blog
The Role AI and Machine Learning Played in Combating WannaCry Download BriefDownload Brief
The Five Generations of Machine Learning in Cybersecurity Download White PaperDownload White Paper
AI Powered Threat Prevention: Exploring a Cybersecurity Revolution Download eBookDownload eBook
Downloadable instructions, applications, and data files referenced in the Intro to AI book. Get the DataGet the Data