Cybersecurity has undergone a radical transformation with the integration of generative artificial intelligence (Gen AI). This technology not only improves threat detection, but also makes it possible to anticipate potential attacks, thus strengthening the digital defense of organizations.

How is artificial intelligence used to detect cyberattacks?

Generative AI analyzes large volumes of data in real time, identifying patterns and anomalies that could indicate an attack. It uses machine learning algorithms to predict malicious behavior and automate responses, reducing incident response time.

Can generative AI create new security threats?

Yes, while generative AI is used to improve security, it can also be employed by cybercriminals to develop more sophisticated attacks. For example, it can generate malware that evades traditional detection systems, which poses new challenges for cybersecurity.

Which companies already apply AI in cybersecurity and with what results?

Companies such as Palo Alto Networks and Microsoft have integrated generative AI into their security solutions. Microsoft, for example, processes billions of signals per day to identify threats at unprecedented scale and speed, significantly improving its defense capabilities.

What are the benefits of generative AI in cybersecurity?

Key benefits include faster and more accurate threat detection, reduction of false positives, automation of incident response and the ability to anticipate attacks before they occur, thus strengthening the security posture of organizations.

Featured use cases of generative AI in cybersecurity

• • Microsoft Security Copilot: This AI-powered assistant helps security teams defend against attacks at the speed and scale of machines.
  • Google Threat Intelligence: Combines Mandiant's expertise and VirusTotal's intelligence with the Gemini AI model to analyze malicious code and provide summaries of findings to more effectively combat threats.
  • Secureframe Comply AI: Provides personalized guidance to remediate failed tests, streamlining compliance and improving security posture.

Ethical challenges and considerations

While generative AI offers numerous advantages, it also presents challenges. Its ability to simulate complex attacks can be used by cybercriminals to develop more sophisticated threats. In addition, automating responses can raise concerns about decision making without human oversight. It is essential to implement ethical and oversight controls to mitigate these risks.

At Qaleon we understand that the cybersecurity of the future is built by working hand in hand with artificial intelligence. That's why our products natively integrate AI to strengthen the protection of organizations, anticipate risks and ensure that every digital decision is made with security and confidence. Because protecting data is not just a necessity, it is a strategic advantage.