Nuisance or unsolicited calls and instant messages come at any time in a variety of different ways. These calls would not only exasperate recipients with the unwanted ringing, impacting their productivity, but also lead to a direct financial loss to users and service providers. Telecommunication Service Providers (TSPs) often employ standalone detection systems to classify call originators as spammers or non-spammers using their behavioral patterns. These approaches perform well when spammers target a large number of recipients of one service provider. However, professional spammers try to evade the standalone systems by intelligently reducing the number of spam calls sent to one service provider, and instead distribute calls to the recipients of many service providers. Naturally, collaboration among service providers could provide an effective defense, but it brings the challenge of privacy protection and system resources required for the collaboration process. In this paper, we propose a novel decentralized collaborative system named privy for the effective blocking of spammers who target multiple TSPs. More specifically, we develop a system that aggregates the feedback scores reported by the collaborating TSPs without employing any trusted third party system, while preserving the privacy of users and collaborators. We evaluate the system performance of privy using both the synthetic and real call detail records. We find that privy can correctly block spammers in a quicker time, as compared to standalone systems. Further, we also analyze the security and privacy properties of the privy system under different adversarial models.

中文翻译：

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privy：多个服务提供商之间的隐私保护合作以打击电信垃圾邮件

滋扰或不请自来的电话和即时消息随时以各种不同的方式出现。这些电话不仅会因不必要的振铃而激怒接收者，影响他们的工作效率，还会导致用户和服务提供商的直接经济损失。电信服务提供商 (TSP) 通常采用独立的检测系统，根据其行为模式将呼叫发起者分类为垃圾邮件发送者或非垃圾邮件发送者。当垃圾邮件发送者针对一个服务提供商的大量收件人时，这些方法表现良好。然而，专业垃圾邮件制造者试图通过智能地减少发送到一个服务提供商的垃圾邮件呼叫数量来逃避独立系统，而是将呼叫分配给许多服务提供商的收件人。自然，服务提供商之间的协作可以提供有效的防御，但它带来了协作过程所需的隐私保护和系统资源的挑战。在本文中，我们提出了一种名为 privy 的新型分散式协作系统，用于有效阻止针对多个 TSP 的垃圾邮件发送者。更具体地说，我们开发了一个系统，该系统可以在不使用任何受信任的第三方系统的情况下汇总协作 TSP 报告的反馈分数，同时保护用户和协作者的隐私。我们使用合成和真实呼叫详细记录来评估privy 的系统性能。我们发现，与独立系统相比，privy 可以更快地正确阻止垃圾邮件发送者。更多，