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.
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.
Modern organizations need a UEM solution that harnesses the power of cognitive technology to deliver enhanced data security, maximize user productivity and increase operational efficiency.
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.
Evolving AI will drive improved security intelligence analytics, while opening up more opportunities for cybercriminals. What happens when AI plays both sides?
As organizations prepare for GDPR in 2018, SecOps and cognitive technology will play crucial roles in helping to ensure improved security without compromising agility.
The top network security trends for security professionals to monitor in 2018 include the evolution of AI, cryptocurrency crime, serverless apps, digital twins, the IoT and more.
If you are planning to launch a new deployment or otherwise expand your security operations center (SOC) in 2018, ensure that cognitive technologies are available to help analysts digest threat data.
The threat landscape is expanding, and organizations must undergo a cognitive convergence to manage evolving security, fraud and operational risks.
Machine learning algorithms can help security teams improve decision-making while conducting user access review and cleanup projects.