C24_Fraudulent Email Address Detection
In this challenge you will take the role of cybersecurity analyst, and see if you can identify emails that are trying to pass as legitimate when they are in fact malicious. You notice that bad-actor emails try to trick the receiver by mimicking major email domains. For instance, you notice that @gnail, @gmial, etc. are trying to pass as @gmail. You then decide to get a count of all the domains: those that have the lowest count have a higher probability of being fraudulent. You must also check whether those low-count email domains are trying to pose as the major emails domains or not. Your answer should not mark @unique.com as fraudulent. Note: Try not to hard-code any variables in your workflow, but instead use mean or median for instance. Hint: Checking for string similarity might help.
Nodes
Extensions
- FeatureKNIME Base nodes
- FeatureKNIME Distance Matrix
- FeatureKNIME Javasnippet
- FeatureKNIME Math Expression (JEP)
Links
- No links available