Given that cyber criminals seem to be waging a rather relentless and damaging online war, AI and machine learning could be the best defense.
After having found application in large number verticals, such as insurance, finance, healthcare, and high frequency trading, machine learning and AI in cyber security are now fast catching up.
Machine Learning and AI in cyber security: what is it
When it comes to cyber security solutions, AI implies the use of machine learning techniques that enable computers to learn from data in a manner similar to humans. Machine learning, a formal branch of AI and computational learning theory, builds systems that learn directly from the data that is fed to them and effectively program themselves to make predictions.
It won’t really be a surprise if machine learning will no longer be optional in cyber security. And the Internet of Things will play a significant role in severely challenging the existing cyber security methodology. Once all those potentially insecure ‘smart’ toaster ovens, cars, and so on start coming online, the amount of data being produced and distributed will significantly increase. And as that happens, the number of weaknesses that can be exploited will also go up tremendously; a challenge that machine learning can perhaps help with.
Machine learning has the capability for 24/7 monitoring and handles larger data loads than any human can deal with. Machine learning greatly reduces the workload of security analysts. What machine learning is particularly good at is identifying and hence filtering out potential threats that expose known patterns, in large quantities. If a subject expert tried and analyzed these patterns, he or she would find them highly complex, involving a large amount of repetitive work. With sufficient amount of samples, machine learning can mimic the decision process of a security expert and can subsequently be deployed at scale to classify new samples.
Machine Learning and AI in cyber security: who’s doing it
There are quite a few enterprises that are deploying security analytics solutions for insights into what’s truly happening inside their organization. And most of these solutions are using AI and machine learning algorithms to generate these solutions.
Early attempts of machine learning at cyber security haven’t met much success when compared with machine learning in other fields. Recently, however, some major companies have acquired machine learning capabilities. This includes Sophos acquiring Invincia, Hewlett-Packard buying Niara, and Radware buying Seculert. This is an indication that some of the major organizations see machine learning as a big asset to cyber security, in the future.
A joint effort by MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and a machine learning startup called PatternEx have entered into a joint effort for the development and improvement of machine learning and AI in cyber security. As a result, they have come up with a system called A12 that delivers a detection rate of 85% and a five-fold decrease in false positives.
IBM’s Watson uses machine learning and natural language processing to reveal insights from large amounts of unstructured data, and is training to learn cyber security practices. Seeing the currents trends, it is more than likely that a collaborative approach between AI, machine learning, and humans will be taken in the foreseeable future.
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