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AI cybersecurity

AI cybersecurity uses machine learning to automatically detect and prevent advanced threats that evade traditional defenses. When evaluating AI security software, look for proven 95%+ accuracy in detecting advanced attacks along with configurable automation to block and contain those threats. Additionally, seek prevention-focused capabilities, flexible deployment options and unified platforms that consolidate XDR, SIEM, SOAR and NTA functions to lower licensing and integration costs.

Vast Data Volumes: AI systems can effortlessly process and analyze vast amounts of data that would be impossible for human analysts, accelerating threat detection and response times. This can help organizations avoid costly breaches and identify new threats.

Improved Situational Awareness and Decision-Making: Often, security professionals are inundated with too much information to effectively understand and address cyber threats. AI can automate routine tasks like monitoring network traffic or analyzing user behavior to free up security talent for more complex and impactful analysis. This enables teams to focus on what matters most and boost their overall performance.

Decreased Risk of Insider Threats: Malicious and accidental insider threats can cost your organization revenue, trade secrets, sensitive data, and reputation. AI can reduce the time it takes to detect and mitigate these risks by proactively scanning for anomalies and risky user behaviors that may indicate malicious intent or unintentional risk.

Discovering Unknown Threats: Cyber criminals continuously develop more sophisticated attack patterns that are difficult for humans to detect and respond to. AI can automatically detect and respond to unknown threats using techniques such as deep learning, which learns a baseline of normal activity and alerts security teams when something deviates from that pattern.