Confusion matrix and Cybercrime
what is the Confusion matrix
A confusion matrix is a table that is often used to describe the performance of a classification model (or “classifier”) means as it is describing the performance so it plays a very important role in ML(machine learning)
There are two types of error in the confusion matrix
- type 1 — This is the most critical error and this is the reason behind cybercrimes, here in type one error it didn’t show alert where it should and that’s why this became very critical
- type 2- this is not that much critical even it good for us
Type1 error is known as FP(False Positive) where our model says that there is no issue be positive but it is actually false, and that makes it very critical for us.
Now, How the Confusion matrix is related to cybercrime?
So, actually what happened is almost every company uses some machine learning models which keep on analyzing the customers viewing the website, and it keeps on analyzing about any DDoS attack, now here we are using ML because we human can’t sit in server for 24hours so we have created ML model which can predict about any attack according to the user behavior, nowhere as we are dependent on the program which guides us related to any attack..sometimes what happens is that someone is trying to attack our server in real but our model say, everything is fine no one is attacking(this came in type 1 error)where our model is giving us false information and saying us to be positive, and at last company have to face that attack
So, FP is a very critical error, every company wants to decrease it as much they can.
Attackers use this FP error in their behavior to attack servers, so this confusion matrix is related to the cyber crimes.
