Machine learning has revolutionized our world. It powers our smart phones, determines which advertisements we view and soon it will dominate the automobile industry through self-driving cars. Even Google now
Making Bayesian Networks Accessible
Bayesian Networks are among the more sophisticated capabilities applied to security analytics, relying as they do on decision science and statistics rather than software engineering expertise. But in many implementations
Most Campuses Have Security Cameras. Now What?
More than 90 percent of all school, university and hospital campuses are now equipped with video surveillance systems, and many of the remainder plan to purchase them in the near
Three Security Analytics Approaches That (Mostly) Don’t Work
Note: This is the introductory post of a five-part series assessing three common security analytics approaches that typically don’t work well. Future articles will examine each of the three in
Putting the Security in Security Analytics
When introduced to the idea of security analytics, most people feel as though they intuitively ‘get it.’ After all, what’s not to like about detailed intelligence that helps you keep your
The Problem with Financial Fraud Detection (and How to Improve It)
By Hannah Hein and Tom Read Financial services institutions use various tools and techniques to prevent fraudulent activity and to quickly mitigate the impact of fraud when it does occur.
Haystax Scientists to Present “Model-First” Framework Enhancements at International Workshops
Papers describe Bayesian probabilistic solutions to insider threat risk assessment and intelligence analysis argument modeling McLean, VA – July 5, 2016 – Haystax Technology scientists will present three papers at
Managing cyber alert overload: how to find high-priority threat signals amid the noise
A new study by FedScoop finds that one-third of government and industry IT professionals surveyed say they receive more than 1,000 cyber-threat alerts per day, with 10 percent saying they
