2020 Market Report: User and Entity Behaviour Analytics Based on Machine Learning - ResearchAndMarkets.com

DUBLIN--(BUSINESS WIRE)--The "User and Entity Behaviour Analytics Based on Machine Learning 2020" report has been added to ResearchAndMarkets.com's offering.

As intrusions employ a wide variety of attack vectors and methods, companies have to seriously consider continuous security monitoring, which provides real-time visibility of users and their devices when they attempt to connect to or work on an enterprise network. Security monitoring gives companies the ability to constantly look over their network and remain a step ahead of cyber threats. Different types of user access should be monitored, examined, and reported to prevent unauthorized use of user credentials, malicious access attempts, simultaneous logins, and activity from multiple geographic locations.

Threats that come from within the organization are the most difficult to detect and the most risky. It is crucial for companies to have security tools that analyse the behaviour of users who are connected to the organisation's network, and entities or endpoints such as servers and applications, to detect anomalies and correlate the threats with users.

Security information and event management (SIEM) tools come into play to cover the detection and collocation puzzle, but they typically lack effective and intelligent threat detection and response. SIEM tools can be bypassed by advanced attackers with relative ease, and focus more on real-time threats than extended attacks.

User and entity behaviour analytics (UEBA) is a vital component of any SIEM system. UEBA tools work with SIEM solutions to provide insights into behavioural patterns within the network. By combining both solutions, companies gain the benefits of threat detection techniques that examine both human and machine behaviour. UEBA tools automate the detection of these attacks with analytics-driven visibility. Artificial intelligence techniques, including supervised and unsupervised machine learning, are applied to data from network security infrastructure. Further, a threat hunting capability improves the speed of threat response and reduces investigation time.

This report reveals the market positioning of companies in an industry using their Growth and Innovation scores as highlighted in the methodology. The document presents competitive profiles on each of the companies based on their strengths, opportunities, and a small discussion on their positioning.

Key Topics Covered:

Strategic Imperative and Growth Environment

• Strategic Imperative
• Growth Environment

Radar Report

• UEBA Based on Machine Learning
• Competitive Environment

Companies to Action

• Darktrace
• Exabeam
• IBM
• LinkShadow
• LogRhythm
• Micro Focus
• Microsoft
• Splunk
• Vectra AI

Strategic Insights

Next Steps: Leveraging the Report to Empower Key Stakeholders

• Significance of Being in the Report
• Empowers the CEO's Growth Team
• Empowers Investors
• Empowers Customers
• Empowers the Board of Directors

Analytics

• Benchmarking Future Growth Potential

For more information about this report visit https://www.researchandmarkets.com/r/ksmquz