Building a modern DDoS solution that is truly effective in thwarting ever-evolving DDoS attacks, to protect all of our customers has been a core tenet for us - enabling us to be an industry leader.
The proliferation of DDoS attacks of varying size, duration, and persistence has made DDoS protection a foundational part of every business and organization’s online presence. However, there are key considerations including network capacity, management capabilities, global distribution, alerting, reporting and support that security and risk management technical professionals need to evaluate when selecting a DDoS protection solution.
Gartner recently published the report Solution Comparison for DDoS Cloud Scrubbing Centers (ID G00467346), authored by Thomas Lintemuth, Patrick Hevesi and Sushil Aryal. This report enables customers to view a side-by-side solution comparison of different DDoS cloud scrubbing centers measured against common assessment criteria. If you have a Gartner subscription, you can view the report here. Cloudflare has received the greatest number of ‘High’ ratings as compared to the 6 other DDoS vendors across 23 assessment criteria in the report.
From our perspective, the nature of DDoS attacks has transformed, as the economics and ease of launching a DDoS attack has changed dramatically. With a rise in cost-effective capabilities of launching a DDoS attack, we have observed a rise in the number of under 10 Gbps DDoS network-level attacks, as shown in the figure below. Even though 10 Gbps from an attack size perspective does not seem that large, it is large enough to significantly affect a majority of the websites existing today.
As we wrapped up the first quarter of 2020, we set out to understand if and how DDoS attack trends have shifted during this unprecedented time of global shelter in place
This quarter, we saw an increasing number of large scale attacks; both in terms of packet rate and bit rate. In fact, 88% of all DDoS attacks in 2020 that peaked above 100 Gbps were launched after shelter-in-place went into effect in March.
Neural networks, as their name implies, are computer algorithms modeled after networks of neurons in the human brain. Learn more about neural networks from Algorithmia.
Recurrent neural networks, also known as RNNs, are a class of neural networks that allow previous outputs to be used as inputs while having hidden states.
The purpose of this project is to build and evaluate Recurrent Neural Networks(RNNs) for sentence-level classification tasks. Let's understand about recurrent neural networks for multilabel text classification tasks.