understanding TP,TN,FP,FN in cybersecurity

In cybersecurity, detecting and identifying threats is crucial. Tools like antivirus software, firewalls, and intrusion detection systems (IDS) are designed to spot and address threats and vulnerabilities. However, the accuracy of these results can vary. Initially, we categorized results as True Positive (TP), True Negative (TN), False Positive (FP), and False Negative (FN), but then we introduced "Benign." Let's define and give examples of each result type:

True Positive (TP)

A True Positive is when a system correctly identifies a threat. For example, if an IDS detects and reports a cyber-attack, it’s a True Positive. This ensures the safety and security of systems.

True Negative (TN)

A True Negative is when a system correctly determines there is no threat. For instance, if antivirus software correctly identifies a file as clean, it’s a True Negative. This prevents unnecessary actions and alerts.

False Positive (FP)

A False Positive is when a system incorrectly identifies a threat. For example, if an IDS wrongly flags legitimate traffic as an attack, it’s a False Positive. This can lead to wasted time and resources.

False Negative (FN)

A False Negative is when a system fails to detect a threat. For instance, if antivirus software misses a virus in an infected file, it’s a False Negative. This can be dangerous as threats go unnoticed.

Understanding these categories helps improve the effectiveness of cybersecurity measures and ensures better protection for computer systems and networks.