In phishing detection, what types of features are fed into the ML model?

The correct choice focuses on features that are critical for identifying phishing attempts using machine learning models. In phishing detection, features like form structure, domain age, and certificate information are particularly significant because they provide essential data points that help the model discern between legitimate websites and fraudulent ones.

Form structure refers to the design and elements of forms on web pages, which can be indicative of phishing. For instance, if a form has fields that ask for sensitive information not typically required by legitimate services, it could be a red flag. Domain age helps identify how long a website has been registered; newly created domains are often associated with phishing attacks. Certificate information relates to the security status of the website, including whether it has a valid SSL certificate. A lack of proper certificate validation can indicate a potential phishing threat.

While other features like network latency, user activity, IP addresses, geographic data, file sizes, and download times can provide context in evaluating potential security threats, they do not directly contribute to the specific identification of phishing cases as effectively as the features outlined in the correct answer. Hence, the emphasis on form structure, domain age, and certificate information makes this choice the most relevant in the context of phishing detection.