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AI cybersecurity uses artificial intelligence (AI) to protect endpoints and networks from cyberattacks. While not a replacement for security professionals, AI can help them by analyzing large volumes of threat data more quickly than traditional methods and identifying patterns that may indicate a breach.

The most popular use of AI in cybersecurity is deploying behavioral analytics to identify threats like malware. This approach monitors the behavior of all users on an organization’s network to understand what “normal” looks like for each person, including where they log in from and what files they access. Then, if a user does something out of the ordinary—like accessing sensitive files at 3 a.m. or logging in from an unfamiliar country—the system can alert security teams to investigate.

Another way AI improves cybersecurity is by automating and streamlining processes and workflows. This allows CISOs and other security leaders to free up their time so they can focus on the most important threats.

However, the integration of AI into cybersecurity can also create new risks. Because AI systems rely on data, they can be vulnerable to tampering and breaches. Attackers can tamper with the architecture, weights and parameters—the core components that determine an AI model’s behavior and performance. Additionally, attackers can conduct adversarial attacks to manipulate the output of an AI model. To reduce these threats, CISOs must ensure their organizations’ AI security is resilient and built with the best practices.