Cyber security practitioners face a dizzying number of threats to infrastructure these days. In fact, the threats by hackers and cybercriminals are becoming so vast in volume, scope, and creativity, that it’s impossible for human protectors to keep their assets secure on an ongoing, minute-by-minute basis. That’s why AI and machine learning have become invaluable as not just a tool for cyber security, but as a core element in cyber and data protection platforms. 

Here is a sampling of four leading-edge AI-driven cyber security companies that are making waves.  

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Fortinet

Fortinet has had a strong presence in AI and machine learning technologies for more than ten years. Its security fabric focuses on areas that benefit end users the most, including monitoring web traffic, gathering data for network operations, tracking malicious web-based campaigns, and zero-day threat protection. 

The company recognized early on that exponential growth in malware volume couldn’t be handled manually, so it adapted to leverage AI and machine learning to support its malware analysts. Its solutions are built to manage:

  • Better threat management scale: massive growth in malware samples led to the creation of an artificial neural network (ANN) for sub-second sample classification. Solutions now analyze millions of samples per day at high levels of accuracy (which would normally require thousands of human analysts). 
  • More accurate predictions: using AI and ML to draw relationships and make predictions, such as comparing two malware infection DNAs and tracing back to the source of a problem. 
  • Faster detection: reducing time to malicious code detection from minutes to sub-second time frames. That’s critical when a widespread outbreak occurs.

Check Point Software

The Israeli-based company has been a pioneer in the field of AI and cyber security, helping its customers customize threat intelligence and select the best solutions to fit specific needs. Instead of developing just one AI-powered cyber security solution, it developed multiple platforms that all work in concert. Among them:

  • Its centralized “campaign hunting” service provides instant and up-to-date attack vectors and strategies to mitigate threats at client sites. 
  • AI analysis tracks ongoing performance and behavior of the cyber security software and reports anomalies to the central system. 
  • The AI engine then collects event data in real-time, helping to prevent attack paths that exploit what may look like unrelated resources, all at the same time. 
  • The threat detection database uses unsupervised learning to reduce the number of false positives and helps to create effective preventative measures against attacks.

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Sophos

Sophos crafted its AI cyber security platform to produce breakthrough technologies in data science and machine learning to improve cyber security. Its AI-based solutions focus on large-scale IT computing architectures, human-to-AI interaction, and the ability to create better information visualization. 

The rise in more sophisticated cyberattacks like polymorphic malware, scripting, and other living-off-the-land cyberattacks has made it easier for hackers to bypass conventional anti-virus defenses that focus on file scanning. To combat this trend, Sophos concentrates on behavior analysis to make cyber defense more robust. It gathers massive volumes of data and a large diversity of behaviors to make it easier to collect and label representative datasets and understand the full context around each behavior characteristic.

Tessian

Email is a common attack vector for a wide range of threats, including phishing, ransomware, account takeover (ATO), business email compromise (BEC), and targeted impersonation attacks. Tessian uses behavioral intelligence modeling, powered by AI and machine learning, to detect and prevent advanced email attacks. Its powerful AI engine analyzes billions of historical email data points to establish trusted patterns of user behavior and relationships, and then warns users of any potentially dangerous anomalies. 

Its AI-driven cyber security engine understands the nuances and context of human relationships and communication patterns on email, and helps see past what is immediately visible in an email to surface telltale signs of a potential attack. And because it continues to learn over time, it can adapt to constantly changing environments. AI capabilities also help protect against both accidental and malicious data loss via email. Historical email data and behavioral intelligence detects email mis-delivery and activity from insiders with malicious intent. 

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Find Out What Skills AI-driven Cyber Security Companies Look For

Whether you’re looking to nurture skills to develop leading-edge cyber security solutions from these and other companies, or implement them to protect corporate infrastructures, the right certifications can help drive you on your quest. Cyber Security Experts are trained on a wide range of skillsets to secure data, run risk analysis and mitigation, architect cloud-based security, and achieve cyber security compliance.

AI engineers are also valuable assets, as they are trained to create practical applications using a wide range of intelligent agents, and machine learning experts are additional assets that master hands-on modeling to create tangible, effective defensive cyber systems. Finally, the Certified Ethical Hacker (CEH) is trained to investigate vulnerabilities in target systems and use the same techniques as malicious hackers, but in a legitimate and legal manner. All are important steps on the path to AI-driven cyber security expertise. 

About the Author

Stuart RauchStuart Rauch

Stuart Rauch is a 25-year product marketing veteran and president of ContentBox Marketing Inc. He has run marketing organizations at several enterprise software companies, including NetSuite, Oracle, PeopleSoft, EVault and Secure Computing. Stuart is a specialist in content development and brings a unique blend of creativity, linguistic acumen and product knowledge to his clients in the technology space.

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