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.
Artificial intelligence (AI) tools enable security teams to identify behavioral patterns that could point to insider threats more quickly.
At RSAC 2018, countless security experts and practitioners gathered in San Francisco to talk about emerging threats and how the cybersecurity industry can prepare to meet evolving challenges.
As AI progresses, security professionals must prepare for the inevitability of machines writing their own malware to infect other machines in the not-so-distant future.