Telecommunications providers face a persistent and evolving array of telecom fraud threats. Among these, Artificial Inflated Traffic (AIT) fraud has emerged as a deceptive tactic that can severely impact telecom operators' revenue, voice traffic quality, and network integrity. Fraud schemes like AIT are part of a broader category of telecom revenue assurance challenges that affect both wholesale and retail voice services.
Artificial Inflated Traffic (AIT) fraud involves fraudulent actors generating fake or artificially inflated volumes of calls, SMS, or VoIP traffic using automated tools like bots, auto-dialers, or SIM farms. These schemes often target termination rates, interconnect agreements, and revenue-sharing models, creating non-human (machine-generated) traffic that mimics legitimate communication patterns.
In essence, fraudsters create phantom traffic or fake call volumes to exploit telecom infrastructure and generate unearned revenue, often leaving operators to foot the bill.
Fraudsters use automated systems to push massive volumes of low-duration, high-frequency calls, or bulk SMS, often via fraudulent SIM farms or compromised VoIP accounts. These attacks target traffic-based billing models and aim to inflate billing metrics while evading traditional detection systems.
Ping Calls focuses on infrastructure abuse; it is fully automated and requires no user interaction. Often involves placing a high volume of extremely short calls that disconnect after just one or two rings, before the recipient answers. These calls do not intend to initiate a conversation but are used to simulate legitimate signaling traffic, often for:
Wangiri fraud is a scam in which fraudsters place massive volumes of brief calls that disconnect before being answered. The difference from basic ping fraud is intent: the goal here is to lure the user into calling back. These return calls, once connected, incur high charges for the caller and generate income for the fraudster through revenue sharing or international call termination payouts.
This makes Wangiri fraud both an AIT method and a consumer scam, targeting:
Used to bypass international routing and inflate local traffic, resulting in SIM box fraud, grey route usage, and revenue leakage.
Bulk, non-human SMS generation, is often triggered by one-time password (OTP) forms, chatbots, or abused APIs on websites.
High-volume robocalls that target test numbers, unused ranges, or premium-rate destinations, leading to auto-dial fraud.
Used to route fraudulent traffic through multiple networks, often exploiting PBX systems, diverted calls, or call chaining.
Attacks that generate synthetic VoIP traffic to inflate VoIP CDRs (Call Detail Records), often involve fraudulent SIP trunking setups.
VoIP PBX systems are vulnerable to unauthorized access, especially when using weak SIP credentials or unpatched software. Once compromised, attackers route mass outbound calls to high-cost destinations, inflating traffic via internal IP-PBX systems, making detection difficult.
Identifying AIT fraud in real time requires more than static rule sets. AI-powered telecom fraud detection systems offer dynamic, adaptive monitoring that can recognize subtle deviations in traffic behavior.
Artificial Inflated Traffic (AIT) fraud requires a multi-layered defense strategy rooted in real-time intelligence and automation. Neural Technologies’ comprehensive Fraud Management System (FMS) combines advanced signaling analytics, fraud detection models, and machine learning to protect operators from evolving attack vectors.
Discover how Neural Technologies’ AI-powered Fraud Management System (FMS) can safeguard your revenue and ensure network integrity.
Contact us today for a personalized demo and take the first step towards smarter fraud prevention.