Identity Guard

Highly scalable system for filtering, fraud detection and enrichment of data from Telco's signaling data

Identity Guard

Identity guard is an adjustable set of services that perform data processing in real time.

It has been refined in several software generations with the objective to improve system performance and throughput.

Main steps in the process are data ingestion, data processing and data delivery. Data ingestion includes collecting data from various sources like TCP/IP streams, CSV files or databases. Data processing consists of the steps like parsing, enrichment, anonymization, filtering and formatting. At the end it delivers data to target systems.

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Fraud detection module

According to a Europol's Europian cybercrime centre, fraud costs the telco industry around €10 billion per year and the amount rises constantly.

In 2020 SMS phishing attacks skyrocketed by more than 328%.  Fraudsters use different methods which target both MNOs as well as customers and vary from infrastructure attacks to social engineering attacks.

Wangiri attacks

Zero-duration calls, mostly to mobile devices, that leave a missed-call number, which is either a premium rate number or one that produces advertising messages 

In more recent cases, bots or scripts initiate fraud by filling out a company's online form with information that leads the companies to call back premium numbers

Interconnect bypass

Using SIM cards from a local carrier and rerouting international calls using a SIM box or GSM gateway

SMS Spam & Phishing

Sending mass SMS in order to obtain personal information from the person who receives the messages

Adding new rules

Identity Guard supports adding new fraud rules and has support of fraud detection exclusion list

RoadMap

H2/2022

Profile Based Fraud

Comparation of recieved data for user and generic fraud signature

H2/2022

H1/2022

In House Fraud

Comparation of billing data with consumption data received from signal network streams

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Protect PII

Protect personally identifiable information by anonymizationusing token rotation and k-anonymity principle.

Enrich or reduce

Enrich data from other sources (like CRM, billing or other systems). Reduce data sets by filtering with rules, consents or blacklists

Enforce consent

Enforce data owner’s consent for each processing purpose. Include or exclude data based on consent status

Reverse anonymization

Control reverse anonymization of PII data securely

Compliance

Recording all actions and processing providing audit trail ensuring company and legal compliance

Notification and alerting

We will alert you of every fraudulent activity or any other suspicious activities recognized by our algorithms

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info@biss.hr

+385 1 389 12 50

Frangeša Mihanovića 9, Zagreb, Croatia