It's hard to believe a computer that couldn't read a newspaper was once considered smart. But as recent innovations in AI for cybersecurity have shown, we are constantly raising the bar for smart.
Just as organizations get comfortable with leveraging the cloud, another wave of digital disruption is on the horizon: artificial intelligence and its ability to drive the cognitive enterprise.
While many CISOs are tempted to invest in as many new technologies as they can find to fight emerging threats, less is more when it comes to minimizing cybersecurity complexity.
By combining repeatable processes for threat hunting with intelligent solutions and skilled analysts, organizations can improve threat response and protect their most critical assets.
Collaborative industry partnerships, a hardened attack surface and a well-practiced incident response plan are all critical in the fight against emerging cybersecurity threats.
The IBM X-Force Red team recently ran into trouble on a black-box penetration testing assignment. Here's how the testers overcame the obstacles to ultimately establish a solid adversarial operation.
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.
As the threat landscape evolves to target connected devices, artificial intelligence (AI) and machine learning will become increasingly crucial parts of any organization's endpoint security strategy.
A recent study conducted by NIST researchers found that face identification performance is optimal when insights from a human expert are combined with a top machine learning algorithm.
Without cognitive insights, a security intelligence platform does little to ease the pressure on short-staffed security operations center (SOC) teams to analyze massive volumes of threat data.