Moving from detection to classification
The transition from malware detection to malware classification represents a significant evolution in the sophistication and granularity of the analysis performed on potentially harmful software. In the realm of malware detection, the primary goal is to identify whether a given piece of software exhibits malicious behavior or not. This typically involves analyzing features extracted from binaries, system calls, network traffic, or other sources to apply a binary decision—benign or malicious. Algorithms used for malware detection focus on distinguishing between these two classes, often employing techniques such as anomaly detection or pattern recognition to flag suspicious activity.
On the other hand, malware classification delves deeper into the categorization and characterization of malicious software, aiming to classify malware into different types or families based on their behavioral patterns, code structures, or other attributes...