Generative adversarial networks are neural networks that compete in a game in which a generator attempts to fool a discriminator with examples that look similar to a training set.
Most organizations around the world lack a consistent incident response plan and thus are unprepared to manage the repercussions of a cyberattack, according to a recent Ponemon report.
By implementing orchestration and automation (O&A), security leaders can deliver the real-time threat intelligence their understaffed analyst teams need to punch above their weight.
A UBA solution powered by machine learning enables security teams to model normal behavior and track subtle changes in user activity to identify malicious insiders.
The traditional mission of security is evolving under the influence of several key trends regarding the functions, staffing, processes and core capabilities of the security operations center.
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.