By augmenting the skills of their human security analysts with machine learning capabilities, organizations can boost the efficiency of their SOCs and stay ahead of evolving cyberthreats.
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.
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.
A recent Cisco study found that more firms are responding to cybersecurity news headlines by investing in artificial intelligence (AI) solutions to safeguard data.
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.
At Think 2018, attendees will learn how an integrated approach to security and resiliency can help them prevent cyberattacks and effectively respond to the ones that slip through their defenses.
A cognitive-enabled mobile device management (MDM) solution can do most of the heavy lifting when it comes to keeping track of devices and the users who access them.
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.