What if I say you that your IoT devices are deceiving you?
A botnet is an ‘internet’ of compromised systems which are controlled by the ‘herder’(owner of botnet). The systems can be compromised by any kind of malware which is executed in your system and allows someone else to control your system. Your may look to be working fine but in actual it may not!
You can also watch my video after reading this article to have a clearer understanding of prevention of botnet attacks using AI.
An interconnected system of compromised IoT devices. These can include compromised CCTV cameras, cell phones, AC..etc.
What can Botnets do
Some of the infamous Botnets
We’ll use Logistic Regression to solve this problem.
The dataset used contains 75000+ samples with 0/1 as ouput. 0 denotes that the data from IoT device isn’t any type of attack. 1 denotes that it could be a tcp/ip flood, spam/junk data.
I downloaded the dataset from UCI Machine Learning Repository and is used by this Research paper.
The Dataset contains 115 features and hence I’ll explain you not what each feature is but how this features are generated.
H: Stats summarizing the recent traffic from this packet’s host (IP)
HH: Stats summarizing the recent traffic going from this packet’s host (IP) to the packet’s destination host.
HpHp: Stats summarizing the recent traffic going from this packet’s host+port (IP) to the packet’s destination host+port. Example 192.168.4.2:1242 -> 192.168.4.12:80
HH_jit: Stats summarizing the jitter of the traffic going from this packet’s host (IP) to the packet’s destination host.
How much recent history of the stream is capture in these statistics
L5, L3, L1, L0, L0.1
I use Deep Learning Studio’s Jupyter Notebooks to train my model on this dataset. It actually comes pre-configured with all the ML/DL frameworks. If you don’t know about it, please check out this.
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Happy Deep Learning.
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