Spam messages are an increasing threat to mobile communication. Several mitigation techniques have been proposed, including white and black listing, challenge-response and content-based filtering. However, none are perfect and it makes sense to use a combination rather than just one. We propose an anti-spam framework based on the hybrid of content-based filtering and challenge-response. A message, that has been classified as uncertain through content-based filtering, is checked further by sending a challenge to the message sender. An automated spam generator is unlikely to send back a correct response, in which case, the message is classified as spam. Our simulation results show the trade-off between the accuracy of anti-spam classifiers and the incurring traffic overhead, and demonstrate that our hybrid framework is capable of achieving high accuracy regardless of the content-based filtering algorithm being used.
- Content-based filtering
- Spam SMS messages
- Threshold sensitivity problem
ASJC Scopus subject areas
- Computer Science(all)