Artificial intelligence (AI) has emerged as an important technology in information security. It can help you automate a lot of core functions, improve your response times, and increase your visibility into emerging threats.
For example, AI-based cybersecurity solutions can offer the most up-to-date knowledge of industry-specific threats. These solutions also give you the power to identify zero-day vulnerabilities and new types of attacks. They also improve speed of detection and allow you to prioritize risks.
Another important area for AI in cybersecurity is security incident management. This means analyzing large amounts of data to make sound decisions. By using AI, you can identify suspicious behavior before it becomes a threat.
Machine learning is a big part of how AI works. This includes anomaly detection algorithms for malicious traffic. In addition, unsupervised learning can be used to detect leaked credentials and activity patterns.
However, artificial intelligence systems are still relatively weak in terms of the quality of their outputs. As a result, they are prone to adversarial examples. Adversarial examples are inputs designed to trick AI systems.
The best AI cybersecurity systems use machine learning to analyze large volumes of data. This helps reduce human error. Moreover, it can be integrated with email security tools to detect suspicious behavior and block potentially malicious emails.
One of the biggest challenges with AI systems is integrating them with an organization’s overall ecosystem. A good AI system needs to be explainable and capable of interpreting its results. Explainability is also key to getting stakeholders buy-in.