Mitigating SMS spam by online detection of repetitive near-duplicate messages

Short Message Service (SMS) spam is increasingly becoming a problem for many telecommunication service providers. Not only do SMS spam messages use mobile network resources abusively, but also in many cases they represent malware propagation vectors for mobile devices. In this work, we propose a network-based online detection method for SMS spam messages. The proposed scheme uses robust text signatures to identify similar messages that are sent excessively in the SMS platform and is robust against slight modifications in SMS spam messages. Additionally, the method uses a fast online algorithm which can be deployed in large carrier networks to detect spam activities before too many spam messages are delivered. It does not store SMS message contents, therefore it does not compromise the privacy of mobile subscribers.