Machine Learning – Taking Your Security Team to the Next Level

Raj Samani, Head of Strategic Intelligence, McAfee LLC
Raj Samani, Head of Strategic Intelligence, McAfee LLC

Machine learning is all around us, enriching our online lives every day. We see it with our own eyes when search engines accurately predict what we’re looking for after we type only a few letters. We feel it protecting our bank accounts evaluating credit card transactions for signs of fraud. We notice it in selections of articles and ads in online newspapers. We no longer think twice about these conveniences; in fact, it’s hard to imagine online life without machine learning.

In relation to cybersecurity, machine learning has been changing the game as a means of managing the massive amounts of data within corporate environments. However, machine learning lacks the innately human ability to creatively solve problems and intellectually analyse events. It has been said time and again that people are a company’s greatest asset. Machine learning makes security teams better, and vice versa. Human-machine teams deliver the best of both worlds.

Machine learning allows endpoint security to continually evolve to stop new attack tactics

Security becomes personal when considering the people behind the attacks, making the human-machine team the best sustaining defence. CSOs empower security operations to blend the best elements of art and science, where security team employees provide creative responses and leverage machine learning to provide high-performance scientific responses. While machine learning can detect patterns hidden in the data at rapid speeds, the less obvious value of machine learning is providing enough automation to allow humans the time and focus to initiate creative responses when responses are less obvious. By using a filter for optimization across the best advantages of human and machine elements, it’s easier to evaluate the relationship between them.

Machine learning adds critical capability to security strategies

The process of security researchers analysing malware to develop signatures is still important, but only as a capability to address the large volume of known malware because it cannot be expected to evolve quickly enough to meet the rapid pace of malware being introduced to the wild. Machine learning becomes the fastest way to identify new attacks and to push that information out to endpoint security platforms. The key differentiator in incorporating machine learning into endpoint security is the amount of relevant data consumed by the algorithms.

Elevate security teams with machine learning

People matter the most, but combining human intelligence with machine-learning technology creates strong security teams. The visibility into tactics throughout the entire attack chain that machine learning affords is critical to enhancing the relationship between security teams and technology. Machine learning enables security teams to devise new defences quickly to adapt to attackers’ automated processes and make it more difficult for them to be effective. Remember, machine learning places the time sequence of activity observed between security products. With machine-learning assistance, security teams have greater insight into who the attacker is, the methods being used, where the attacks are coming from and how they are spreading, as well as which security measures are working and which are being defeated.

Most importantly, the presentation of machine-learning results enables people in security teams to do what they do best – create intelligent, innovative and effective solutions to new threats before significant damage is done to the business. If people are the company’s greatest assets, then machine learning helps make them even greater.

To close, machine learning should be a critical component of an enterprise’s endpoint security strategy. Given the volume and evolution of attacks hammering away at endpoints, security must be able to adapt without human intervention, and must provide the visibility and focus to enable humans to make more informed decisions. Machine learning has come of age with big data driving accuracy up and false positives down. The proof of successful human and technology teaming will be seen in the ability to rapidly dismiss alerts and accelerate solutions to thwart new threats. Your users deserve the best that cybersecurity has to offer, and today the best endpoint security products leverage machine learning.