×

You are using an outdated browser Internet Explorer. It does not support some functions of the site.

Recommend that you install one of the following browsers: Firefox, Opera or Chrome.

Contacts:

+7 961 270-60-01
ivdon3@bk.ru

Methods of differential anonymization of data based on a trustworthy neural network for protecting bank customers personal information

Abstract

Methods of differential anonymization of data based on a trustworthy neural network for protecting bank customers personal information

Serezleev D.S., Abaev Yu.K.

Incoming article date: 17.10.2025

The article discusses modern methods for protecting bank customers' personal information based on differential anonymization of data using trusted neural networks. It provides an overview of the regulatory framework, analyzes technological approaches and describes a developed multi-level anonymization model that combines cryptographic and machine learning techniques. Special attention is paid to balancing between preserving data utility and minimizing the risk of customer identity disclosure.

Keywords: differential anonymization, trusted neural network, personal data, banking technologies, information security, cybersecurity