Protection
Protection
one million connections per square kilometer.
Protection
device density that are essential for edge computing.
Protection
easier to manage, deploy and use.
Protection
costs and bandwidth consumption and increased
network responsiveness.
Use Cases Include: Robocall / Nuisance Call Detection and Revenue Share Fraud (IRSF and Wangiri)
Beyond traditional types of voice fraud, such as Revenue Share Fraud (IRSF) and Wangiri (missed call) fraud, fraudsters have begun to leverage SIP architectures for fake call centers and robocalls which has led to major damage for mobile subscribers. Fraudulent activity has caused a dramatic drop in legal enterprise voice traffic, leading to multiple regulator initiatives on preventing Caller ID spoofing and robocalling. This problem is not limited to any geography and is slowly spreading across Europe, Asia, and the Middle East, as regulators prepare to step in and force Communications Service Providers (CSPs) to take action.
Protection from Robocalls, Nuisance Calls, IRSF, Wangri and Fraudulent Call Centers
CSPs can no longer rely on using only rules and thresholds for detection, as fraudsters themselves are using state-of-the-art technology to avoid detection such as artificial intelligence to change behavior in real-time and CLI Spoofing for more successful Robocall attacks. By using Quantum Ran’s native ML algorithms to identify fraud and other anomalous network behavior, reliance on rules can be avoided, providing higher accuracy, lower false positives, and the knowledge that known, future, and unknown types of fraud will always be quickly identified. CallShield’s framework allows flexible control of all processing and decision stages via rules leveraging both ML and Rule-Engine technologies.
Real-Time Detection
Fraudulent Call Centers
CallShield’s ML supports dedicated features for fraudulent call centers, operating from dedicated bases and generating mass nuisance calls to subscribers. These call centers are often focused on specific frauds or scams.
ML features support dedicated detection of these call centers in operation, including outbound call rate, declining call rate, voicemail durations, and call origin
RoboCalls/Nuisance Calls
Within CallShield, features used by ML include classifying abnormal traffic peaks, regular interval ranges, anomalous behavior classification, answer rates, voicemail redirect rates, typical duration patterns, social graph analysis, and other unknown anomalies. Dedicated detection of neighbor spoofing, mirror spoofing, and enterprise spoofing techniques are also supported. ML identifies this traffic for detailed monitoring, and analyzes all calls, the caller-id initiates to callee’s sharing the same range. Deep LSTM and CNN networks review entire neighborhoods holistically to identify Robocall / Nuisance.
CLI Spoofing
Protection against CLI Spoofing is supported with prebuilt spoofing detection techniques. CLIs are examined to identify inaccuracies that may indicate spoofing, such as CLI lengths that are too long or too short, or even of an incorrect format or from an unallocated number range or fixed area code. CLI origination can also be examined to determine the validity of local CLI’s originating from an offnet interconnect by performing on-net presence checks.
Wangri, and Voice Fraud (IRSF)
CallShield features used with ML include identifying sudden increases in traffic. Detection factors include typically uncommon destination, time of calls, history of communication from the number, duration, time between calls, connection length, roaming status, IMEI change, and average call duration.
Signaling Firewall from Quantum Ran Addresses:
- Protection of subscriber sensitive data (e.g., network identifiers like IMSI)
- Prevention of subscriber location tracking by an attacker
- Detect and prevent voice call interception attempts
- Detect and prevent SMS interception
- Prevention DoS attacks on the subscribers
- Malicious packet detection
- DoS attacks on operator equipment prevention
- Discovery of the new threat vectors through traffic profiling and ML
Additional Solutions
Environment Quantum Ran’s CEO Pardeep Kohli, outlines the company’s
vision for an open and interoperable network future in a live
interview at MWC 2022.
for investment in private 5G.
made the next-generation IMS (NIMS)project a reality.
services, and advanced technologies available today
that power 5G.