Machine Learning Used To Detect Cyber Attacks

The digital world is growing exponentially as time passes. And as it is expanding, we are discovering its true potential and value. But the yin and yang concept is also prevalent in the internet domain. So, there’s evil in good here too, as cyberattacks loom over everything digital.

Where machine learning was utilized in cyber security to spot similar malware and malicious links, instead with cyber crime it’s wont to evade filters, bypass CAPTCHA checks, and generate targeted phishing emails. When comparing the 2 , cyber security appears to possess far more consolidated uses for machine learning. But future trends towards evasive malware and phishing may pose a significant threat to the cyber security industry.

Cyberattacks have become a growing threat and are problematic for the government, business organizations, as well as individuals. According to a 2019 report, malware attacks were approximately 10 billion in the year 2018. What’s even scarier is that as technology strengthens, cybercriminals develop with it.

As a result, they get to enhance their skills and trick you seamlessly. Cyberattacks have the potential to not only disturb businesses but also inflict serious damages on one’s technological resources. But how does machine learning detect cyber attacks? And how are these two related?

Well, the traditional network monitoring tools do not work anymore. Hence, it is essential to look for new and advanced methods to detect as well as prevent cyber attacks. This is precisely where machine learning kicks in!

So basically machine learning algorithms have the ability to classify unseen data as well as predict the future of that data, which means that it has a variety of uses in cybersecurity. However, the same features of machine learning can also be used in malicious contexts.

Let’s Begin with What Machine Learning Is?

Machine learning is essentially a method of data analysis that automates analytical model building. It can also be defined as a branch of artificial intelligence that stems from the notion that systems have the potential to identify patterns, learn from data as well as make decisions with minimum human intervention.

In Machine learning, computer algorithms are studied to ameliorate the use of data and experience. Moreover, machine learning is also known as part of Artificial Intelligence.