Although AI is poised to take a much larger role in cybersecurity future trends, this doesn't necessarily mean fewer opportunities for human analysts. In fact, it could mean quite the opposite.
To move toward deep, advanced security analytics, CISOs should replace their fragmented tools with a platform-based approach that can leverage a broad set of data.
Machine learning can strengthen your security posture, but it's not without its blind spots. What do adversarial machine learning attacks look like, and how can companies stop them?
Law firms tasked with analyzing mounds of data can vastly improve their efficiency by using legal AI tools.
As a young girl in Romania, Irina Nicolae was fascinated with machinery and how different parts fit together. Today, she conducts AI research to develop ways to protect this technology from threats.
Topics of discussion at this year's Black Hat conference included the Internet of Things (IoT) in smart cities, the latest advancements in vulnerability management and more.
IBM developed a new AI-enabled voice assistant to respond to common questions across email, corporate contacts and calendar using natural language processing (NLP) capabilities.
According to a new study conducted by the Ponemon Institute and sponsored by IBM, organizations could save an average of $2.5 million in operating costs by deploying artificial intelligence (AI).
Despite the risks quantum computing might pose to organizations, this emerging technology also promises to enhance cybersecurity capabilities such as SIEM, incident response and data protection.
Today's security teams lack the time, talent and resources to keep up with the rapidly evolving threat landscape. AI can automate tedious processes and take some pressure off security analysts.