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Antivirus, Anti-Malware Lead Demand for AI/ML Tools

Companies are attaching the term “AI” to everything these days, but in cybersecurity, machine learning is more than hype.

DARKReading
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Artificial intelligence and machine learning tools are gaining traction in enterprises, and the rate of adoption is particularly notable in cybersecurity operations, where these technologies are being used to improve enterprise security posture, according to Dark Reading’s latest research on enterprise cybersecurity.

Dark Reading’s Artificial Intelligence and Machine Learning in Cybersecurity survey found that enterprises are using AI and ML in a range of cybersecurity technologies, such as firewalls, endpoint detection and response platforms, security information and event management systems, and network traffic analyzers. Antivirus/anti-malware was the only security technology enhanced with AI and ML that was used by more than half of the respondents (51%). This is not surprising, as back in 2017, practitioners were already beginning to implement AI/ML in corporate antivirus measures.

Cybersecurity professionals have to match the bad actors who are sourcing AI/ML technologies for their purposes. The arms race between CISOs and their adversaries may be driving adoption of tools with AI and ML capabilities in areas such as phishing detection (49%), threat detection and response (45%), and endpoint security (40%). One third of the AI/ML integration in real-world security teams comes in the form of malware analysis (38%), intrusion detection and prevention (35%), threat intelligence (35%), identity and access management (34%), network security/network traffic analysis (33%), vulnerability management (32%), and security information and event management (31%).

About a quarter of respondents mentioned using AI/ML in user behavior analytics/predictive analytics (27%), fraud detection (27%), automated security operations (26%), and automated incident response (25%). While that is still a sizeable chunk of companies, the slightly lower adoption rate suggests that this grouping represents developing features.

For more on the impact of AI/ML on cybersecurity, download the Dark Reading report “The State of Artificial Intelligence and Machine Learning in Cybersecurity.”

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