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Across industries, AI is being woven into a vast array of systems to automate and improve current processes. In the case of cybersecurity, AI is being used to analyze logs, predict threats, read source code and identify vulnerabilities.

While these tools can help reduce human error and streamline processes, they also open up new attack surfaces for adversaries. To mitigate these risks, it’s crucial to follow responsible AI practices including robust security measures, transparent and ethical development, ongoing monitoring and a role for humans in critical decision-making processes.

When selecting an AI tool, start by mapping your security goals, operational needs and budget. Then, evaluate how the solution integrates and scales with your existing system infrastructure. Look for a provider with a track record of reliability and performance as well as a clear roadmap for future features and models.

Detecting Threats

AI-based security solutions use machine learning to analyze data and pattern recognition to identify anomalies in behavior. This can help security teams quickly recognize and thwart unauthorized access or data exfiltration. Some solutions also use natural language processing (NLP) and entity behavior analytics (UEBA) to recognize sensitive information in documents, images and non-textual sources.

Using machine learning, AI-based threat intelligence solutions can learn over time to recognize patterns in the behavior of different attackers. This can help security teams spot phishing campaigns or malware samples that may have previously passed undetected by traditional methods. This helps CISOs develop and test responses before they’re needed, saving time and resources.