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AI is revolutionizing cybersecurity, but it’s not without its risks. Join world-class engineers, researchers and product leaders as they cut through the hype to bring you the latest on the latest trends, challenges and threats in the realm of AI security.

Reduced Risks

Detecting and responding to security threats is often complex, costly and time-consuming. AI technology can help streamline and automate processes to reduce the risk of human error and enable organizations to take faster, more effective action against cyberattacks.

Enhance Authentication

AI solutions that use machine learning (ML) algorithms can better understand how users communicate, identify textual patterns and other typical behavior to protect against more sophisticated threats like spear phishing attacks. They also help block malware and other threats by analyzing software based on its inherent characteristics — for example, if a piece of software is designed to encrypt many files rapidly or if it targets high-profile individuals like company CEOs.

Endpoint Security

AI-powered security systems can proactively monitor and protect all types of endpoints, including computers, smartphones and Internet of Things (IoT) devices. They create baselines of normal behavior for each type of endpoint and quickly detect any deviation, enabling them to prevent a range of advanced or zero-day threats that require specific signature updates, like malware, ransomware and cryptojacking.

Integrated ML solutions are also critical to optimizing data protection processes such as encryption and tokenization, and identifying vulnerabilities before hackers exploit them. However, implementing AI tools can expand an organization’s attack surface, and it’s essential to consider the privacy and security implications of each component of an AI solution.