A BEHAVIOR-BASED BIOMETRICS VERIFICATION USING MACHINE LEARNING TECHNIQUES AND METHOD THEREOF

Abstract

The present invention relates to a behaviour-based biometrics verification using machine learning techniques and method thereof. The present device comprises a data collection module configured to gather behavioural data from user interactions with a computing device, a feature extraction module configured to extract one or more behavioural features from the behavioural data, the features corresponding to user-specific behavioural patterns, a machine learning model trained to recognize user-specific behavioural patterns, wherein the machine learning model is configured to classify whether the behavioural features match a pre-established user profile and a verification module configured to authenticate the user based on the classification output from the machine learning model. Accompanied Drawing [FIG. 1]

Specification

Description:[001] The invention, in general, relates to the technical field of machine learning. More specifically, the present invention relates to a system for behaviour-based biometrics verification using machine learning techniques and methods thereof.
BACKGROUND OF THE INVENTION
[002] The following description provides the information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[003] Traditionally biometrics like fingerprints, facial recognition, and iris scans rely on physical traits, which can be compromised if stolen or altered under certain conditions (e.g., injuries, aging, or environmental factors). Existing methods for authenticating users on touchscreen devices typically involve entering a password or PIN or drawing a specific geometric pattern on a grid. However, because these devices are fre , Claims:1. A system for verifying the identity of a user based on behavior-based biometrics, comprising:
a data collection module configured to gather behavioral data from user interactions with a computing device;
a feature extraction module configured to extract one or more behavioral features from the behavioral data, the features corresponding to user-specific behavioral patterns;
a machine learning model trained to recognize user-specific behavioral patterns, wherein the machine learning model is configured to classify whether the behavioral features match a pre-established user profile;
a verification module configured to authenticate the user based on the classification output from the machine learning model.

2. The system as claimed in claim 1, wherein the behavioral data comprises at least one of typing dynamics, mouse movements, touchscreen gestures, gait analysis, voice patterns, or device handling patterns.

3. The system as claimed in claim 1, wherein the feature extraction module extracts a

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