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AI cybersecurity

Amid a constantly changing IT security landscape, cyber attacks have become more frequent, sophisticated and difficult to detect. Infosec professionals must work harder than ever to keep up with the latest malware and breaching tactics. As such, many companies are leveraging AI cybersecurity to enhance their existing systems and protect their business assets.

AI cybersecurity uses advanced machine learning, deep learning, and other predictive analytics technologies to quickly analyze massive amounts of data and identify anomalies that may indicate a cyber attack. The technology can also automate threat detection and response, reducing costs by eliminating manual processes.

However, cybersecurity experts must continue to monitor and assess AI systems for potential weaknesses or vulnerabilities. They should also use regular security assessments and penetration testing to ensure the system’s infrastructure, algorithms, and data handling processes are secure. Additionally, they should implement secure development practices and establish robust logging and monitoring mechanisms for their AI solutions.

One example of an AI cybersecurity solution is ExtraHop’s Enterprise Immune System, which monitors network traffic and identifies abnormal patterns that could indicate a cyber attack. This platform reduces time to detection from minutes to sub-second time frames, enabling businesses to respond to threats more quickly.

Another popular AI cybersecurity solution is Palo Alto Networks’ Next-Generation Firewall, which employs a combination of AI and other predictive analytics technologies to protect against complex threats. Its intelligent security platform detects attacks across the entire IT environment, including networks, cloud environments, and endpoints.