As the volume of cyberattacks grows, security analysts are always on their heels to provide a shield. To address this issue, developers are showing interest in using Machine Learning (ML) to automate threat-hunting. As a sub-field of machine learning, unsupervised learning is making a footprint in detecting malicious content. Resisting cybersecurity challenges with machine learning is not a new thing. Researchers have been working on it since the late 1980s.

Artificial intelligence and machine learning hold great promise for both defenders and attackers, making it one of the most important security trends to follow in 2020, says Gerald Beuchelt, the CISO of LogMeIn.* No matter how many brilliant security professionals and analysts you have in an organization, humans just can't keep up with the data processing, analysis and other tasks required to prevent attacks. That's why, when considering trends in cyber security for 2020, artificial intelligence (AI) and its subset machine learning should not be ignored. Here are some of the machine learning and artificial intelligence trends to pay attention to in 2020. According to a recent Capgemini report, 51% of organizations have a high utilization of AI for detection of cybersecurity threats.

The U.S. must offer a "measured response" to Iran's downing of an American drone over the Strait of Hormuz, according to a Republican member of the House Homeland Security Committee. Failure to respond to Iranian aggression would incentivize future attacks, U.S. Rep. Mark Green, R-Tenn., told Shannon Bream on Thursday on "Fox News @Night." "I think we clearly need a measured response here," Green said. "I think the world needs to see, honestly, smoke and fire. I think Kim Jong Un needs to see smoke and fire. There's been an attack on the U.S. military and if we don't respond, we are incentivizing future attacks."

Security system that look at past attacks to help deal with future ones are deeply flawed. Here's an alternative approach that uses the latest machine learning tech. It's no secret that there's a constant game of cat and mouse playing out between hackers and security experts, with both sides working their hardest to stay ahead of the other. While hackers and assorted cyberattackers are always on the lookout for new vulnerabilities to exploit, however, unfortunately security systems can be a bit backwards looking in their approach -- relying on digging back in the archives to try and see how future hacks may play out. That's what Antigena, a machine learning security system developed by British cybersecurity startup DarkTrace is trying to change.