Artificial intelligence covers everything from machine learning to business intelligence. Machine learning, in particular, has become a highly useful tool in our modern work environment. Machine learning, in short, means you can make machines learn from data and make decisions without explicitly telling them, what to do.
Machine Learning Helps Us Find New Attacks
Cyber security is one of the key domains, where machine learning is extremely helpful. Cyber security companies deal with a lot of data and high dimensionality of data. Machine learning is at its best in processing huge volumes of data, and processing data fast.
Linda Liukas explored the wonders of AI and machine learning with some of our experts in the new episode of Adventures in Cyberland:
Traditionally, cyber security has protected companies against threats we have seen before. But the cyber threat landscape is getting more complicated. It is difficult to build a rule for something we don’t know to exist. Machine learning systems can be trained to find attacks, which are similar to known attacks. This way we can detect even the first intrusions of their kind, and develop better security measures.
Machine Learning as a Building Block in Cyber Security Solutions
The most established cyber security companies have a long history of utilizing AI. F-Secure’s researcher Andrew Patel says:
Cyber security companies have been using data science techniques to process and analyze large collections of both historic and fresh threat intelligence data for many years. F-Secure have been utilizing machine learning algorithms to solve classification, clustering, dimensionality reduction, and regression problems for over a decade, and nowadays, many of us use data science techniques in our everyday work. Recent advances in neural network architectures, such as generative adversarial networks, have opened new and interesting paths to solving problems in the cyber security space. We’re enthusiastically exploring many of these new paths right now.
Detection and response solutions are an excellent example of the use of AI and machine learning. At F-Secure, we collect billions of events every month from our customers’ computers. Only a fraction of these events are real attacks. Machine learning helps narrow down the number of events to a level a human can handle. It is then possible to identify the real attacks and contain them quickly.
Included in the Endpoint Detection and Response (EDR) service, F-Secure’s Broad Context DetectionTM uses real-time behavioral, reputational and big data analysis with machine learning to automatically place detections into context. It evaluates the risk levels, affected host criticality and the prevailing threat landscape to understand the scope of a targeted attack. Machine learning is an integral building block of the EDR service. It helps detect and respond to targeted attacks efficiently.
Will robots replace cyber security experts in the future?
No, robots will not be taking over the world. Human experts will always be needed. Machines can never replace certain human skills, such as creativity, ability to understand new things and figure out what to focus on. There are things machines are good at, like going through a vast amount of data, pointing out the topics that are interesting and making decisions fast. That’s why we will need both.
Matti Aksela, F-Secure’s VP of Artificial Intelligence, describes the future role of a cyber security expert as a “Cyber Centaur”. This means combining the best sides of man and machine to protect customers better. According to Aksela, cyber criminals are most likely using AI as well. They might, for example, want to learn which phishing emails work best, how to hide inside the target network for months and how to automate their actions. Because AI is used on both sides, “the good” and “the bad”, it will be even more important that the man and the machine work together and learn from one another in the future, too. To make better cyber security solutions.