Exploring Anti-Spam Models in Large Scale VoIP Systems

P. Patankar, Gunwoo Nam, G. Kesidis, C. Das
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引用次数: 19

Abstract

Although the problem of spam detection in email is well understood and has been extensively researched, a significant portion of emails today are spam. A most widely used method to detect spam involves content filtering, where the spam detector scans the received email for keywords. However, the same approach cannot be applied to detect Voice over IP (VoIP) spam, since a call has to be categorized as a legitimate or a spam (each to a degree with a certain reliability) before the connection is established. Also, spammers over IP can potentially generate orders of magnitude more spam volume, at far less cost, and with greater anonymity than telemarketers using the Public Switch Telephone Network (PSTN). The spam problem in VoIP is further compounded by the absence of a do-not-call-list, which has been the main reason for the reduction of spam calls in PSTN. Thus, the spam issue for VoIP is as important as those pertaining to quality-of-service (QoS) of the voice traffic itself. To this end, we propose two different anti-spam frameworks for large scale VoIP systems. The first one is a centralized SIP-based spam detection framework that relies on SIP messages during the call establishment phase to identify spam calls, and the second one is a distributed referral social network model, where a user is assigned a reputation score by its neighbors. Based on the reputation, a callee can decide either to accept or decline a call. Our simulation results indicate that the referral model can provide better anti-spam capabilities by isolating a spammer faster than the SIP based approach, and can also correctly identify spam calls over 98% of time.
探讨大规模VoIP系统中的反垃圾邮件模型
虽然垃圾邮件的检测问题已经得到了很好的理解和广泛的研究,但今天的电子邮件中有很大一部分是垃圾邮件。检测垃圾邮件最广泛使用的方法是内容过滤,即垃圾邮件检测器扫描收到的电子邮件中的关键字。但是,同样的方法不能用于检测IP语音(VoIP)垃圾邮件,因为在建立连接之前,必须将呼叫分类为合法呼叫或垃圾呼叫(每种呼叫在一定程度上具有一定的可靠性)。此外,通过IP发送垃圾邮件的人可以潜在地以比使用公共交换电话网(PSTN)的电话营销人员更低的成本和更大的匿名性产生数量级的垃圾邮件量。由于没有不接电话列表,VoIP中的垃圾电话问题进一步复杂化,这是PSTN中垃圾电话减少的主要原因。因此,VoIP的垃圾邮件问题与语音流量本身的服务质量(QoS)问题同样重要。为此,我们针对大型VoIP系统提出了两种不同的反垃圾邮件框架。第一种是集中式的基于SIP的垃圾邮件检测框架,它在呼叫建立阶段依赖SIP消息来识别垃圾邮件呼叫;第二种是分布式推荐社交网络模型,其中用户由其邻居分配信誉分数。根据声誉,被呼叫者可以决定接受或拒绝来电。我们的模拟结果表明,通过比基于SIP的方法更快地隔离垃圾邮件发送者,推荐模型可以提供更好的反垃圾邮件功能,并且可以在98%的时间内正确识别垃圾邮件呼叫。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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