Machine learning (ML) used to be a tool limited to specialized developers and dedicated teams. Now, thanks to many web service providers and approachable tooling, your applications can use pre-build learning models and machine learning techniques the same way you would use any web service API. This is a quick way to test out and benefit from machine learning without having to invest in artificial intelligence, building your own learning models, or shaping your application around ML.

Everyone at Splunk is very proud of the amazing things that our customers and partners do with their data. It is always extra special when one of those organisations is really doing good and looking after us all in our daily lives. I’m delighted to share one of those stories from the Derbyshire Fire & Rescue Service (DFRS) who is using Splunk as its data-driven SIEM.

One of the great things about developing for Splunk Security Essentials is that most of the features and capabilities are requested from customers and the security community. In this latest release (3.1), we added a feature that has been requested frequently: the ability to filter the ATT&CK Matrix for Cloud and SaaS Techniques. The MITRE ATT&CK Framework consists of multiple matrices such as Enterprise, Mobile, and ICS.

Internal audit and compliance departments benefit from having a comprehensive framework to use to perform corporate risk assessment and internal control testing as well as fight fraud. The most popular framework is the COSO Framework. The Committee of Sponsoring Organizations of the Treadway Commission (COSO) was originally formed in the United States in 1985 to combat corporate fraud.

Innovations in technology have been a prime agent for disruption throughout much of human history. Advancements in materials science gave English archers, with their superior longbows, the advantage over the French in many conflicts during the Hundred Years War; such as the Battle of Agincourt. In the late 2000’s, the music industry was forced to reinvent itself in the face of changing consumer consumption models as a result of technological advancements or become irrelevant.