Pattern matching is a rule-based technique that looks for recognizable shapes in input, such as keywords, signatures, regular expressions, or fixed message structures. It does not understand meaning the way a human does; it simply checks whether the current input fits known patterns. Early conversational systems like ELIZA relied heavily on this kind of logic to respond convincingly without real comprehension.
In cybersecurity, pattern matching is a basic but important defensive tool. Antivirus engines, intrusion detection systems, spam filters, and web application firewalls often compare traffic or files against known malicious patterns. The weakness is that attackers can evade simple rules by changing spelling, encoding, spacing, or structure. That is why pattern matching works best as one layer in a larger defense strategy, paired with behavior analysis, anomaly detection, and human review.