Which method focuses on matching known patterns to data for security?

The correct response relates to the technique employed in security that leverages known patterns to analyze and detect anomalies in data. Statistical or lexicon methods work by identifying deviations from established norms or known vocabulary, which is particularly useful in recognizing threats such as malware signatures or attacks that match specific characteristics.

In security contexts, this might involve the analysis of code, user behavior, or network traffic. By employing statistical analysis, organizations can create models based on historical data that define what is normal, thereby allowing for the detection of suspicious activities that do not conform to these patterns. This approach can effectively identify potential breaches or security incidents based on previously recognized indicators.

The other methods listed do not directly emphasize the pattern-matching aspect. Document matching typically refers to comparing documents for similarity rather than focusing on data patterns for security purposes. Network traffic decryption is about deciphering encrypted communications, which does not inherently involve pattern matching. Finally, a policy template serves as a guideline or framework for security practices, rather than a mechanism for analyzing patterns in data.