Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Detect Ransomware in Your Data with the Machine Learning Cloud Service

While working with customers over the years, I've noticed a pattern with questions they have around operationalizing machine learning: “How can I use Machine Learning (ML) for threat detection with my data?”, “What are the best practices around model re-training and updates?”, and “Am I going to need to hire a data scientist to support this workflow in my security operations center (SOC)?” Well, we are excited to announce that the SplunkWorks team launched a new add-

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.

Technology Webinar: ImmuniWeb Application Security Platform

ImmuniWeb® Application Security Testing Platform leverages a machine learning technology for intelligent automation of web vulnerability scanning. Complemented by human intelligence, it detects the most sophisticated web application vulnerabilities and comes with zero false-positives SLA.