To increase their margins, unscrupulous operators or their accomplices may use bots and automation to generate large volumes of fake SMS traffic through various apps or websites. These messages often contain OTPs, sent to both real and non-existent mobile numbers. As a result, both the resource owners and the A2P SMS providers suffer. The former incur financial losses from the fake messages sent on their behalf, while the latter risk reputational damage from the spamming.

The Artificial Traffic Detector (ATD) is designed to identify and block SMS AIT fraud, preventing it from reaching mobile network operators (MNOs). By utilizing machine learning (ML) algorithms that analyze the metadata of the SMS flow and the content of the messages, ATD can detect suspicious activity and swiftly halt the campaign. This way, they take care of both their traffic integrity and their enterprise customers.

Overview

The solution efficiently accumulates statistical data on traffic flow within a designated "window" and makes informed decisions based on this data (while also utilizing SMS metadata). This dynamic approach ensures the system adapts to real-time traffic conditions, optimizing performance by gathering sufficient statistical insights before activating filtering. In an AIT campaign, this process allows for a brief initial period during which messages are processed as data is collected (typically between 20 and 50 messages) to enable precise and effective filtering thereafter.

ATD processes incoming messages by intelligently separating them into distinct streams based on SMS metadata. This approach allows the system to effectively group similar traffic (campaigns), ensuring that filtering mechanisms are applied with precision and tailored to each specific stream, optimizing overall performance.

of SMS flow to identify fraudulent activity

to efficiently adapt to changing fraud patterns

to handle large volumes of traffic

with any SMS platforms via HTTP

from being deceived by fraudulent SMS flow and paying for fake messages

by blocking fraud attempts and preventing system overload caused by a large volume of artificial traffic

and negotiating advantage as a trusted provider for both MNOs and enterprise customers