Which of the following best describes botnet detection?

Botnet detection refers to the process of identifying networks of compromised machines, also known as 'bots,' which are potentially under the control of an attacker. These networks are often used to carry out various malicious activities, such as distributed denial-of-service (DDoS) attacks, spamming, or stealing data. The detection of a botnet involves analyzing traffic patterns, command-and-control communications, and unusual behavior that indicates a number of computers are coordinated to act together, often without the owners' knowledge.

The focus is on recognizing the infected devices that have been hijacked to form a network that can execute tasks instructed by a malicious actor. This is critical for maintaining cybersecurity, as botnets represent a significant threat and can cause serious damage to both individual organizations and the broader internet ecosystem.

The other choices represent different areas of cybersecurity that do not encompass the specific nature and purpose of botnet detection. Detecting financial fraud pertains to analyzing transactions for indicators of deception, monitoring user behavior on a single device focuses on individual user actions rather than networks of devices, and filtering spam emails involves managing unwanted communications rather than identifying compromised systems. All of these facets are important in cybersecurity, but they do not directly align with the specific objective of detecting botnets.