Merve Sahin and Aurélien Francillon
Telephone networks form the oldest large scale network that has grown to
touch over 7 billion people. Telephony is now merging many complex
technologies (PSTN, cellular and IP networks) and enabling numerous
services that can be easily monetized. However, security challenges for
telephony are often neither well understood, nor well addressed. As a
result, telephone networks attract a lot of fraud. In this talk, we will
systematically explore the fraud in telephone networks, focusing on
voice telephony. We will present a taxonomy of fraud, and analyze two
prevalent fraud schemes in more detail: looking into the ecosystem of
International Revenue Share Fraud (IRSF), and discussing a new
countermeasure to the well-known problem of voice spam.
This talk aims to improve the understanding of the fraud ecosystem in
telephony networks. We first provide a clear taxonomy that
differentiates between the root causes, the vulnerabilities, the
exploitation techniques, the fraud types and finally the way fraud
As concrete examples, we first look into International Revenue Share
Fraud (IRSF), where phone calls to certain destinations are hijacked by fraudulent operators and diverted to the so-called ‘international premium rate services’. This fraud often involves multiple parties who collect and share the call revenue, and is usually combined with other
techniques (such as voice scam, mobile malware, PBX hacking) to generate call traffic without payment. We will further explore the IRSF ecosystem by analyzing more than 1 million `premium rate' phone numbers that we collected from several online service providers over the past 3 years.
In the second part, we will look into voice spam, a prevalent fraud in
many countries. After giving an overview of various types of unwanted phone calls, we will focus on a recent countermeasure which involves connecting the phone spammer with a phone bot (“robocallee”) that mimics a real persona. Lenny is such a bot (a computer program) which plays a set of pre-recorded voice messages to interact with the spammers. We try to understand the effectiveness of this chatbot, by analyzing the recorded conversations of Lenny with various types of spammers. As we consider the ‘benefits’ as a fundamental part of our fraud definition, we believe that chatbots can be combined with the existing fraud detection and prevention mechanisms, as a supplementary way of slowing down voice spam campaigns.
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