Automation, Machine Learning and Artificial Intelligence to defend against emerging threats

Malware sophistication is increasing as adversaries begin to weaponize cloud services and evade detection through encryption. This is used as a tool to conceal command-and-control activity. To reduce adversaries’ time to operate, security professionals said they will increasingly leverage and spend more on tools that use AI and machine learning. This has been reported in the CISCO annual cybersecurity report. The report also shows 50 percent of organizations in India are reliant on automation, 53 percent are reliant on machine learning, 51 percent are highly reliant on AI.

While encryption is meant to enhance security, the expanded volume of encrypted global web traffic (50 percent as of October 2017) - both legitimate and malicious - has created more challenges for defenders trying to identify and monitor potential threats. Cisco threat researchers observed more than a threefold increase in encrypted network communication used by inspected malware samples over a 12-month period globally.

Applying machine learning can help enhance network security defenses and, over time, “learn” how to automatically detect unusual patterns in encrypted web traffic, cloud, and IoT environments. Some of the 3,600 chief information security officers (CISOs) interviewed globally for the Cisco 2018 Security Capabilities Benchmark Study report stated they were reliant and eager to add tools like machine learning and AI, but were frustrated by the number of false positives such systems generate. While still in its infancy, machine learning and AI technologies over time will mature and learn what is “normal” activity in the network environments they are monitoring....Read More