Skip to 0 minutes and 8 seconds In this video, I’ll try to show you how to reverse stress test the network that we created in the first video tutorial. So reverse stress testing is looking at your network and then trying to figure out how you can break it down. And in our case this network was all the websites and those tracking it. And here you see it, the server, our network. And now you can see that some of these trackers are connecting the different nodes in our network. Now, let’s just pick one and– Google Analytics– and block it. So you can actually block one node before you clear all the data. And let’s pick a very well connected node here. So this is our first.
Skip to 0 minutes and 59 seconds And then we’ll click Reset Data. And, yes, we’re sure we want to do this now. Just reset it. And notice at this Google Analytics is still blocked. Our next step, we’ll follow the link in the article to Adblock Plus. And edit Firefox. Adblock Plus is an add-on that will block out advertisements. But also it will block out some of the websites that are tracking your activities on the internet. So this is a bit of a general stress test for our network here. So now we’ve deleted or blocked the most popular node and maybe some extra nodes. Now I’ll just reload all the websites that I had open so that they’ll show up again in Lightbeam.
Skip to 2 minutes and 7 seconds All right, and let’s see, what does our network look like now? There you go.
Skip to 2 minutes and 17 seconds Some parts of it are still connected. But it’s much less connected. It looks much less like a network. So this was a little reverse just for our network here that consisted of the websites that we visited and websites that were tracking us. And I think that we learned from this the reverse stress test that– and that block– and blocking out one of the major nodes here was actually a way to severely reduce this network. So if we want to keep this network more stable, we might want to limit people who are blocking this or not instal Adblock.
Skip to 3 minutes and 0 seconds So I hope this was a way that you could get a bit of a feeling for what a stress test, and in this case, the reverse stress test of a network can be like.
Extra: Reverse stress testing your internet data collection network
This video is a continuation of the earlier example on internet data collection. The purpose is to provide an example of stress testing a network. This includes downloading free software and you should in no case purchase any software for this. In the previous extra activity we have explored the network of those who track us online. Now let’s see what happens if we would break this network. Let’s perform our own small reverse stress test on this network.
As mentioned in the previous lecture reverse stress testing means thinking about how to break down the network in question. In this case, a network of connected websites tracking our information.
Besides our earlier Firefox and Lightbeam software we will use another free Firefox add-on called Adblock Plus to break down our network. Adblock blocks advertisements from showing on webpages and blocks trackers from accessing you. This way, trackers won’t be able to see which webpages you visit. Find out more on their website.
Remember: you will have to disable this add-on yourself, if you do not want to keep using this after completing this task.
Let’s get started
In the video above we show how you can reverse stress test your tracking network by destroying highly connected nodes. Using the Lightbeam software you can disable individual nodes while Adblock is a more general approach as it blocks some trackers.
What did you find out?
So you have seen what an extremely simple reverse stress test might look like. What would a normal stress test look like? Maybe in this case applying a shock to a highly connected node would qualify as a stress test, but please do not try this at home.
But more importantly we hope you got a feeling for network theory and network stress testing. It basically boils down to looking at what happens to the network when certain nodes are taken out.
© University of Groningen