Method and System for Detecting Spam Source of Phone Service
Original Publication Date: 2008-Feb-28
Included in the Prior Art Database: 2008-Feb-28
This disclosure provides a method and system for dectecting spam source of phone service The disclosure includes Calling Information Collectors (CIC), which will residents in the callee’s devices and collect the users’ behavior information and terminal parameters and spam analyzer, which receive and coordinate the CICs’ events and execute the SPAM judgment function.
Method and System for Detecting Spam Source of Phone Service Method and System for Detecting Spam Source of Phone ServiceMethod and System for Detecting Spam Source of Phone Service
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"Spam" can be defined as unsolicited bulk communications or calls and email sent to groups of recipients who have not requested it. Spam is a major problem that plagues communication networks. Not only dose it hog expensive network resources but reduces productivity by wasting precious man-hours. The openness of traditional network and the evolution of voice over IP (VoIP) technology will cause the call spam severer.
There are several known solutions for call spam.
A feasible way to combat spam is to make them illegal. But it is no clear to define what makes a call unsolicited. There is also some doubt whether such legislation will be effective in VoIP environment because it is hard to enforce legislation across national boundaries.
Blacklists and whitelists have a limit success in curbing Email spam and could be extend to call spam. But it is hard to keep the lists updated and some people, like the business man, want to accept calls from just about anyone. However, used in conjunction with other spam-avoidance schemas, they provided good protection against serial spammers and ensure that known callers are always connected.
Call pattern analyses to identify spam are proposed to identify possible VoIP spammers, and one of such technology is gray-leveling. A caller that attempts to make more that a pre-defined threshold of calls over a time period is considered to be a spammer. Moreover, current network hardware would be unable to accurately identify spam from millions of legitimate voice calls in real-time.
A challenge-response test is used to identify robot-caller, usually spammer, by applying a Turing test on the caller. The failure of test causes the call to be ended. Turing test is effective but to change millions of legitimate voice call flows to add a challenge-response test is un...