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AI cybersecurity leverages artificial intelligence to strengthen cyber defenses. These solutions enhance threat intelligence, reduce false positives and automate routine tasks to help security professionals focus on the more challenging work of analyzing and responding to threats.

Strongly Consider Security Automation

Often, the fastest response to a cyberattack is through automated remediation that shuts down access or blocks suspicious activity as soon as it’s detected, minimizing damage and mitigating risks. This is the core of what many security-focused AI tools offer, and it’s an especially important feature for addressing high-risk incidents like ransomware attacks.

Assess the tool’s ability to automate a broad range of processes, including log analysis, vulnerability scanning and patch management, threat hunting, and other tasks that would be time-consuming or impractical for human analysts. Look for a solution that can perform these functions without sacrificing performance or accuracy and enables you to integrate the software into your existing systems, avoiding disruption.

A strong solution should also enable you to customize and configure the security rules that govern how the system behaves, providing flexibility to adjust to your specific business needs and the unique threat landscape. It should also provide improved context for prioritizing alerts, enabling faster incident response and helping you address potential root causes to prevent future attacks.

Invest in AI that can interact with your current technology infrastructure and support multiple platforms, including integrated XDR and SIEM solutions. It should also support a robust data validation process, so it can verify the validity of the models used and identify potential biases. The LF AI & Data Foundation’s Adversarial Robustness Toolbox is one of the most widely-used free tools for this purpose, and it provides an open, customizable framework for evaluating the security of ML models.