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.
While fraudsters have yet to master adversarial AI, the only way for the security community to get ahead of the emerging threat is through collaborative defense.
Today, IBM introduced the Resilient Incident Response Platform (IRP) with Intelligent Orchestration and X-Force Threat Management services to help organizations connect human and machine intelligence.
Security analysts can maximize the effectiveness of their incident response capabilities by integrating disparate tools such as database firewalls and UBA with a strong SIEM solution.