Machines Gives Cybersecurity a Big Boost

06 Feb Machines Gives Cybersecurity a Big Boost

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Machines Gives Cybersecurity a Big Boost

Machine learning will no doubt continue its rapid evolution, but it’s already given us a number of very important improvements in cybersecurity.

Machine Learning has made tremendous advancements during the last few years. It has become an integral part of our lives. Online shopping has evolved to the point where nearly every site we visit will recommend items we may want to purchase. Machine learning makes that possible based on our recent searches, viewing, and purchases. Streaming video sites recommend movies based on our entertainment habits, and news sites analyze our previous interests to tailor the articles they present us. Sophisticated controls can automatically land specially equipped airplanes. Self-driving cars are becoming a reality.

All this is made possible by machine learning technologies that can turn massive amounts of unstructured data into meaningful, actionable information. Machine learning systems are much faster and more efficient than people, and they are increasingly becoming more accurate than their human counterparts.


Machine Learning is Extremely Important to Cybersecurity

Effective security requires monitoring massive amounts of data. The vast amounts of security related data that is generated every day in most corporations is astonishing. I’ve yet to encounter a security analyst that wasn’t overwhelmed trying to keep up the workload.

Consider the job of an analyst responsible for an incident where a network has been penetrated in multiple places and malware is stealing sensitive information. The analyst in this case is charged with multiple tasks. He must discover what exactly has been stolen, how it was done, and repair the system to prevent the same or similar attacks again. That’s an awful lot of work, especially under the pressure of a system under serious attack.

Fortunately, machine learning has evolved to the point where it is helping security analysts in numerous ways. We’re starting to see new technologies that do a better job digesting large amounts of data and compiling it into meaningful, concise data points for the security staff. This saves hours or even days of manual effort, and often produces better results.

In some cases, machine learning technologies can recommend or even undertake precise and detailed actions as a response to significant threats. For example, a well-trained machine learning model could identify unusual user behavior such as unauthorized connections, and in some cases, shut them down as they occur.

A well-trained machine-learning based product can identify new types of malware that other technologies miss, and quarantine these malicious objects before they cause damage.

Machine learning will no doubt continue its rapid evolution, but it’s already given us a number of very important improvements in cybersecurity.

Click here to learn more about Fortscale and how it uses machine learning to detect malicious and abnormal insider behavior.

Rodolfo Melgoza is the Marketing Manager at Fortscale.
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