To defend their confidential data from increasingly sophisticated cybercriminals, security teams must leverage machine learning to perform analytical tasks that are too tedious for humans to complete.
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Instead of waiting around for an incident to occur, organizations of all sizes need an application security testing program based on a fundamental understanding of risk management.
A recent Cisco study found that more firms are responding to cybersecurity news headlines by investing in artificial intelligence (AI) solutions to safeguard data.
In an age of limited physical interaction, organizations need a way to establish digital trust without compromising the user experience.
Researchers have devised ways to manipulate speech recognition systems to carry out hidden commands, suggesting that cybercriminals will soon develop similar ways to exploit this technology.
Security professionals need a comprehensive way to analyze user behavior, automatically respond to reports of suspicious activity and manage user access accordingly to thwart insider threats.
Today, IBM announced IBM Security Guardium Big Data Intelligence, a solution that provides the power and capacity of a big data platform while also meeting data security requirements. Expanding data volumes and longer compliance data retention...
Evolving AI will drive improved security intelligence analytics, while opening up more opportunities for cybercriminals. What happens when AI plays both sides?
While the rise of AI has stoked fears of job loss in many industries, security professionals have something new to worry about: AI cyberattacks.
The threat landscape is expanding, and organizations must undergo a cognitive convergence to manage evolving security, fraud and operational risks.