Threat hunting can help organizations transition from reactive to proactive defense strategies and start thinking like cybercriminals.
Two researchers performed an experiment based on billions of log lines that demonstrated the importance of domain expertise in machine learning analysis.
AI2 uses an "analyst-in-the-loop" system to improve itself and a "human-in-the-loop" system to create examples to be used in iterative training algorithms.
Machine learning systems like A12 are designed to augment human analysis with cognitive intelligence, enabling IT professionals to reduce false positives.
If a threat model assumes a system is operating within certain parameters, changes in the threat environment could trigger unintended second-order effects.
The IBM X-Force Threat Research team is keeping watch on all things retail during the upcoming Black Friday through Cyber Monday shopping weekend.
The NSF is sponsoring an attempt to build a malware chip capable of detecting anomalies in system processes and alerting local security software.
Threat monitoring is an essential practice for any security program, but there are many approaches that can be taken when embracing this strategy.
Excessive false positive detection can impair users' ability to perform basic functions or administrative actions, producing results akin to an attack.
A recent survey indicated that security professionals in the financial industry were overly confident in their breach detection capabilities.