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The need for AI-enhanced and automated security solutions for better threat prevention, detection & response
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Artificial intelligence (AI) and machine learning (ML) have been adopted widely across industries over the years due to the multi-faceted benefits that the technologies bring about. AI and ML have been also increasingly adopted across industries, from healthcare, education, information & communication technologies (ICT), logistics, maritime, aviation, aerospace & defence, entertainment & gaming, etc. Particularly, AI and ML have been used widely in cybersecurity industries, by either bad guys and security communities, making the security landscape even more sophisticated. Most of organizations, regardless of size, are now facing greater challenges in the day-to-day security operations. Many of them indicate that the cost for threat management, particularly threat detection and response, is too high. The AI-driven attacks are increasing in number and frequency, requiring security professionals to have more advanced, smart and automated technologies to combat these automated attacks. The increasing challenges in security operation nowadays suggest the need for a smarter, adaptable, scalable, automated and predictive security strategy to deal with the constantly evolving threats more effectively. AI/ ML has been increasingly developed by security companies to strengthen their competitiveness. Most of them now have been in the midst of developing their own AI/ ML algorithm to empower their security products, either in certain product or all of product lines. AI and ML have been used in all stages of cybersecurity to enable a smarter, more proactive and automated approach toward cyber defense, from threat prevention/ protection, threat detection/ threat hunting, threat response to predictive security strategy. Security startup companies are the most proactive in AI-security technologies with a great deal of number of AI-enabled security technologies introduced to the market. However, large traditional security companies have also beefed up their strategies to keep up with the trend of forging AI/ ML into their existing security solutions.There are hundreds of companies now in the market with different capabilities and focused areas, from application-centric protection, AEDR, to security analytics platform. In this report, we profile those companies that are AI/ML-driven and AI/ML-centric cybersecurity companies.This research is delivered by Frost & Sullivan cybersecurity research and practice team. The key questions this study seeks to address are:1. What are the needs to adopt a smarter and holistic security framework?2. What key role the AI and ML are expected to paly in the cyberseurity ?3. How AI/ ML are adopted in cybersecurity? 4. What are the use cases for AI/ML in cybersecurity? 5. What are the key features and differentiators among AI/ML-driven security vendors’s solutions?
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