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  /  Cybersecurity   /  Top 10 Cybersecurity Companies Using AI to the Fullest in 2022
Cybersecurity companies

Top 10 Cybersecurity Companies Using AI to the Fullest in 2022

Here’s an elite group of innovative cybersecurity companies building AI into products in order to defeat attackers and win customers

The emergence of IoT devices with the integration of cutting-edge technologies like artificial intelligence and computer vision has made significant growth in cybersecurity measures. Multiple cybersecurity companies are gaining popularity to combat cyberattacks in companies. There are different cybersecurity companies using AI that can protect internet-connected systems or other IoT devices. AI and machine learning can help augment a company’s cybersecurity by constantly monitoring for any suspicious activity and correcting the problem before it takes effect. Let’s explore some of the top cybersecurity companies using AI to the fullest in 2022.

 

CrowdStrike

CrowdStrike is a relatively new name in the cybersecurity market. The business started up in 2011 and is officially called CrowdStrike Holdings, Inc. Its key security system is called CrowdStrike Falcon and this combines both cloud and on-device elements. The secret weapon of the CrowdStrike Falcon system is an AI-based detection system, known as user and entity behaviour analytics (UEBA). The UEBA concept is one of the major innovations that has thrust the system security industry forward, escaping the flawed AV detection model that had started to let too many new viruses onto devices.

 

Darktrace

Darktrace developed its enterprise immune system as a platform for all of its cybersecurity products. EIS uses AI methodologies and populates status rule bases through unsupervised machine learning. The first thing that EIS needs to do when installed on a network is to establish a baseline of normal activity. This is termed the “pattern of life” in Darktrace terminology. Traffic pattern for each network, the activity of each device on the network, and the behaviour of each user are modelled to provide this record of standard conduct.

 

SAP NS2

Spun off from SAP in 2005, SAP NS2 uses data analytics and fusion technologies from SAP and applies them to cybersecurity, working with a number of US security agencies and corporations. Their AI and ML technology helps national security professionals process troves of data and protect sensitive information passing through a variety of locales. In addition to their work with defence industry customers, SAP NS2 systems also handle the hard work of securing supply chains, which often involves dozens of companies operating in a variety of scenarios. The company also uses AI and machine learning to protect cloud platforms for a number of different customers.

 

Vade Secure

Vade Secure is one of the world’s leading email defence companies, deploying artificial intelligence and machine learning to protect more than 600 million mailboxes in 76 countries from a variety of threats including spear phishing, ransomware, and malware. With the funding, we will continue to invest in our AI-based threat detection engine and build on Vade’s leadership in email security for ISPs.

 

Cynet

Cynet deploys AI in its network threat detection systems that examine threats and act on them automatically. The ethos at Cynet is to make advanced threat protection as straightforward as running any system monitoring package. Cynet has one product, called Cynet 360. This is a complete cybersecurity system that includes AV endpoint protection through device detection, threat prediction, user behavior modelling, and vulnerability management.

 

Webroot

Webroot harnesses the power of AI to stop zero-day threats in real-time, securing businesses across the globe with threat intelligence, and providing protection for endpoints as well as networks. The company uses machine learning to gain more insight into specifically why certain attacks are bad, in an effort to expand its understanding of the threat landscape.

 

FireEye

FireEye was founded in 2004 and specialized in threat research and recovery consultancy services. This is a labor-intensive field of work and didn’t make the company any money. Through innovation and acquisition, the company has moved into the production of cybersecurity tools that use AI to monitor networks and spot anomalies. This strategy, together with moving from a fee-based structure to a subscription ‘Software-as-a-Service’ has made the business profitable and turned what was beginning to look like an overrated novelty into a sought-after investment.

 

Callsign

Callsign uses AI and ML to validate a person’s identity just from a swipe on a touchscreen, number of keystrokes on the keyboard, number of locations, and other activities. The company’s trademark platform, intelligence-driven authentication, combines multi-factor authentication and fraud analytics powered by deep learning technology to fight against fraudulent activity, from identity fraud to SMS phishing.

 

Blue Hexagon

Founded on the belief that deep learning will fundamentally change cybersecurity, Blue Hexagon offers customers real-time network threat protection that can deliver threat detection in less than a second. Blue Hexagon uses AI to create malware based on global threat data and the dark web, all in an effort to test its own systems and push its capabilities to the limit. Blue Hexagon’s systems work in networks and in the cloud, covering a variety of threats across a multitude of different platforms.

 

Cylance

Cylance started out as an independent cybersecurity company, but since November 2018, it has been a division of BlackBerry Limited. Cylance began its existence in 2012 at a base in Irvine, California. It is reputed to be the first cybersecurity protection provider to apply AI to its system. The company became a leader in the field of IPS. Key early backers included Dell Ventures, CapitalOne Ventures, and Insight Venture Partners.