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SIP HEADER BASED FEATURE EXTRACTION FOR SPIT ATTACKS IN A COMPREHENSIVE ANTI-SPIT FRAMEWORK

机译:基于SIP标题的特征提取,用于综合反吐框架中的SPIT攻击

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VoIP (Voice over Internet Protocol) is gaining popularity due to its manifold advantages and is currently a major technology used in Wireless voice communications. This popularity has made VoIP networks attractive to the users, who use VoIP facilities to generate numerous commercial phone calls or messages (spammers). This vulnerability is named Spam over Internet Telephony (SPIT) and is assumed to be as one of the most important future threats to VoIP networks. In this paper a comprehensive solution for effective SPIT detection, is presented. The proposed framework, is a combination of effective recent solutions, besides new implementations in a modular system. The implemented modules do only rely on the features which are extracted from the SIP header information. Overall decision upon an incoming call is made in a weighting process which yields excellent decision ability. Finally, if the certainty percentage of the decision was not acceptable enough, an interferential subsystem with Audio CAPTCHA prevents the spitter to access the destination phone number. In order to test the proposed framework, the behavior of the Spitters with different skills, is simulated. Furthermore, an efficient evaluation technique is proposed which has overcome the fact that there is no valid universal SPIT database and has demonstrated the success of the presented solution.
机译:VoIP(互联网语音协议)由于其歧管优势而获得普及,目前是无线语音通信中使用的主要技术。这种受欢迎程度使VoIP网络对用户有吸引力,谁使用VoIP设施来产生众多商业电话或消息(垃圾邮件发送者)。此漏洞在互联网电话(SPIT)上被命名为垃圾邮件,并被认为是对VoIP网络的最重要的未来威胁之一。本文提出了一种有效吐检测的综合解决方案。除了模块化系统中的新实现之外,拟议的框架是有效最近解决方案的组合。实现的模块仅依赖于从SIP报头信息中提取的特征。在来呼叫时的整体决定是在加权过程中进行的,从而产生了出色的决策能力。最后,如果决定的确定性百分比不够,则具有音频CAPTCHA的干扰子系统可以防止SPITTER访问目的地电话号码。为了测试所提出的框架,模拟了具有不同技能的点分类的行为。此外,提出了一种有效的评估技术,这已经克服了没有有效的通用吐制数据库的事实,并且已经证明了所提出的解决方案的成功。

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