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DDoS protection goes to Machine Learning!

Updated: Jul 18, 2020

DDoS prevention great way to protect your applications within your organisation cloud or on-premises applications!

What DDoS is mostly, it is a diversion, where the hacker usually tends to be already in and while you are trying to recover from the attack, the attacker moves laterally within your systems exfiltrating your data or trying to make your services "jailed" by using data encryption with their own keys and afterwards trying to blackmail your organisation to pay for your data. Such in TalkTalk hack or the largest attack towards Finnish Government, where it took 15 days to fully recover from the attack.

The most common attack is a SYN flood (TCP); traffic that comes from unprotected IoT botnets, but there are UDP attacks as well. What this does to your applications and services is that those will be unreachable for users or very slow.

With Machine Learning prediction that takes approx.2 weeks to learn your application environment and behaviours, the malicious attacks can be prevented in a very sophisticated manner and the remediation can be automated. The traditional way is to block the IPs without any threat intelligence, but by strict policies. This unfortunately may block the users that are actually valid. Why DDoS prevention with Machine Learning is better is because it is more than black/white listing.

During my years at operator, there was quite many times, when the basic DoS occurred. Even though the attacks were not distributed, we had full work to block the traffic manually from the backbone routers as at that time there were no DoS prevention mechanisms, the solutions were implemented later on.

If you are interested in hearing more about technology-neutral solutions regarding DDoS protection, please do not hesitate to contact


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