A VoIP anti-Spam System based on Reverse Turing Test

Abstract

A reverse Turing test based anti-voice-Spam scheme in conjunction with black/white listing is proposed, demonstrated and verified to mitigate the Spam threats to the security of a VoIP network. The first part of this work demonstrates the feasibility of VoIP Spam generation and routing without going though a proxy server. The second part studies the implementation and evaluation of using a reverse Turing test to detect the spams, as well as the Turing-like challenge design considerations.

It is demonstrated in this thesis that VoIP spam can be automatically generated and routed without the involvement and control of a proxy server or registrar. Without specific SIP configuration knowledge of the target phone, a fake INVITE message was sent to the target and a SIP session was successfully established to broadcast spam messages. This was also verified by the test result from monitor and simulation software SIPp. In the process, an automatic UDP port scanner was implemented to find the listening port of the victim machine.

The VoIP spam detection system consists of two components, a regular SIP based VoIP softphone and a challenge selection & grading program. The challenge is a randomly picked voice question from a pool of pre-recorded questions designed by the user. A set of challenge design guidelines was discussed particularly for the application to a VoIP environment. The reverse Turing test was implemented and evaluated for usability, correctness and performance merits. The time requirement for installation and configuration is short. About 75% of evaluators used less than 10 minutes to install and configure our tool. The experimental results show the program works well with a high passing rate for human users and a low passing rate for the machine users. Over 86% evaluators who speak English as the 2nd language passed the English audio challenge based VoIP anti-Spam filter, whereas around 96% of native speakers pass the tests. On the other hand, the A.I. chatter robot in our experiments failed 98% of the challenges. Also the resource consumption of this system is very little. According to the reports we received from users, the average disk space consumes about 4.63 MB.