Federal Cybersecurity: 2018 is the Year of AI

While pundits in all manner of fields are predicting that 2018 will be the year where Artificial Intelligence (AI) comes into its own, that promise really will hold true in cybersecurity, and particularly in the federal government.

As we’ve seen time and again over the last few years, the federal government has been the target of an unrelenting barrage of cyberattacks and while these attacks are not always successful (see: WannaCry), there are still far too many that penetrate the national digital fortress. This is not to level any criticism against the acting federal CISO or his agency peers.

Not only are the attacks against federal agencies constant, but the tools that they have inherited are woefully inadequate. While traditional cyber defenses might be able to detect a certain range of attacks – often referred to as the “known-knowns” – they are blind against the unknown. The attacks that haven’t been seen before are the very ones that do the most damage.

Moreover, the need to provide far more robust and sure security to federal agencies is assuming an even greater importance, as agencies look to take advantage of technologies such as voice integration and the myriad of possibilities in the Internet of Things (IoT) to deliver on the mission much more cost effectively and intuitively. We’re talking about securing all interactions and data, from delivering citizen-services via home assistants, like Alexa, to protecting the warfighter while in theater.

While these are brilliant and necessary innovations, they also dramatically expand the attack surface for adversaries. Not only does this mean that security must be incorporated into the architecture of networks and systems, but that unless we can integrate a much smarter form of security, our cybersecurity teams will tie themselves in knots chasing red herrings and failing to (Read more...)

This is a Security Bloggers Network syndicated blog post authored by Chris Zimmerman. Read the original post at: Cylance Blog