Cyber Crimes & Confusion Matrix
What is Cyber Crime ?
Cybercrime is criminal activity that either targets or uses a computer, a computer network or a networked device. Most, but not all, cybercrime is committed by cybercriminals or hackers who want to make money. Cybercrime is carried out by individuals or organizations. It is an unlawful action against any person using a computer, its systems, and its online or offline applications. The fraud did by manipulating computer network is an example of Cybercrime.
Various types of Cyber crime attack modes are as follows
- Hacking
- Denial Of Service Attack
- Software Piracy
- Phishing
- Spoofing
Cyber-crime is defined as either a crime involving computing against a digital target or a crime in which a computing system is used to commit criminal offenses.
WHAT IS CONFUSION MATRIX?
A Confusion matrix is an N x N matrix used for evaluating the performance of a classification model, where N is the number of target classes. The matrix compares the actual target values with those predicted by the machine learning model. This gives us a holistic view of how well our classification model is performing and what kinds of errors it is making.
The above table has the following cases:
- True Negative: Model has given prediction No, and the real or actual value was also No.
- True Positive: The model has predicted yes, and the actual value was also true.
- False Negative: The model has predicted no, but the actual value was Yes, it is also called as Type-II error.
- False Positive: The model has predicted Yes, but the actual value was No. It is also called a Type-I error.
CYBER-SECURITY WITH CONFUSION MATRIX
An intrusion detection system (IDS) is a necessity to protect against network attacks. The system monitors the activity within a network of connected computers in order to analyze the activity for intrusive patterns. Should an `attack’ event happen, then the system has to respond accordingly. The detection rate and false alarm rate are the two important measure for IDSs, however, several other measures are also reported on such as confusion matrix, classification accuracy, and AUC (area under curve).