Machine Learning


What are the top misconceptions about machine learning?

Many businesses are now talking about artificial intelligence (AI), and specifically machine learning, as a way to solve data problems more effectively. In theory, this sounds easy. What could be better than using AI to get a computer to learn how to solve a problem over time, without manual intervention? The reality is very different, however.


The Role of AI and ML in Preventing Cybercrime

According to a seminal Clark School study, a hacker attacks a computer with internet access every 39 seconds. What’s more, almost a third of all Americans have been harmed by a hacker at one point or another, and more than two-thirds of companies have been victims of web-based attacks. A 2020 IBM study showed that the total cost of data breaches worldwide amounted to $3.9 million, which just may sound the death knell for many businesses affected by breaches.

Calligo launches world's first managed service to make machine learning accessible to any business

Fully managed machine learning service handles entire management, cleanliness and governance of data, avoids costs associated with data science recruitment, and delivers more accurate insights twice as fast as AWS and Google.

Cybersecurity Experts Discuss: Machine Learning for Security Applications

In a discussion between Ben Harrison, Director SOC and Security Services at Cygilant and Jake McCabe, CISSP, Presales Director at LogPoint, we summarize why machine learning and a SOC go hand in hand. Traditional SIEMs offer a rules-based approach as it looks for alerts. Because you can easily write a search, it’s very good at picking out known-bad entities. However, there are certain things that can occur which are not so black and white.


How Siemplify Uses Machine Learning to Drive SOC Efficiency

The promise of machine learning in cybersecurity, specifically inside the security operations center, is vast, but let’s not get ahead of ourselves. Machine learning can’t solve all your problems. Yet if you’re using the Siemplify Security Operations Platform, machine learning is playing an increasingly prominent role.

The Netacea Approach | Smarter Bot Management Powered by Machine Learning

The majority of internet traffic is now made up of bots. Many bots are malicious, and actively looking for the next opportunity to attack. In fact, bots make 90% of all login attempts. They also pretend to be human, trying to bypass security measures and evade detection by mimicking human behaviour. Worse, the old defences aren’t enough on their own. Manual analysis, rules-based defences and web application firewalls just can’t keep pace with the ferocity of these attacks.

What is Machine Learning?

Over the last century, our technology devices have gone from being clunky systems that require tons of human interaction, to modern machines that seem to have a mind of their own. Our phones can do things like autocomplete sentences before we finish typing, suggest purchases based on sites we’ve visited in the past, and even predict our schedules on any given day based on our prior habits. This is all possible due to the growth of artificial intelligence and machine learning.


Machine Learning Protects Employee Privacy & Data Security

How Machine Learning Helps With Privacy and Data Security. Both data attacks and data security have evolved tremendously over the past few years. Notable advancements have been made in artificial intelligence that can improve your information security, while preserving privacy for your employees.


What Machine Learning Means For Security Operations

Over the past two years machine learning has found its place firmly in the cybersecurity industry and its benefits are indisputable. Through machine learning, we’ve seen great improvements implemented into technology that can make tangible improvements to our cybersecurity posture. Cybersecurity marketers have also gotten hold of machine learning and it has become the buzzword du jour in many respects.