There is a gaping hole in the digital defences that companies use to keep out cyber thieves. The hole is the global shortage of skilled staff that keeps security hardware running, analyses threats and kicks out intruders. Currently, the global security industry is lacking about one million trained workers, suggests research by ISC2 - the industry body for security professionals. The deficit looks set to grow to 1.8 million within five years, it believes. The shortfall is widely recognised and gives rise to other problems, says Ian Glover, head of Crest - the UK body that certifies the skills of ethical hackers.

Nominet today announces turing 1.3, the latest iteration of its DNS visualisation and analysis tool. The update adds a wide range of capabilities and enhancements to the platform, foremost of which is a new machine learning algorithm that allows turing to learn and understand the network analytics pattern of the user's business. The new functionality will be of huge benefit to cyber security experts and CIOs as it acknowledges the reality that enterprise networks aren't neat and structured environments where a simple security policy is enough to deliver protection, but a dynamic place where patterns and threats emerge and evolve on an ongoing basis. With these features, turing is the only product offering near real-time DNS traffic filtering and analysis down to the packet level, at enterprise performance and scale. Machine learning in turing makes use of third-party security feeds, which allows the tool to cross reference IP addresses and query names with known bad actors, and then provide the user with an overview of the top 10 events in their DNS traffic they need to know about at any one time.