# Secure Learning Management System Based on User Behavior
## 1 Introduction  
Biometrics is the mechanism of recognizing a person through their distinctive features. This mechanism refers to physical and behavioral characteristics. Biometrics based on physical characteristics measures a static feature that does not change over time, such as fingerprints, face recognition, or hand, palm, or iris geometry. When it is based on behavioral characteristics, biometrics measures a person's features through the way they act, such as voice recognition, signature verification, keyboard dynamics, or mouse usage dynamics [1; 2; 3]. The advantage of biometrics based on physical traits is the high accuracy it presents in comparison to behavioral biometrics. However, additional equipment is required for the implementation of physical biometrics, leading to certain limitations, such as the high cost of purchasing the devices. Behavioral biometrics is a method often used for authentication, but it produces insufficient accuracy as the behavior is unstable and can change over time. Identification and verification are the goals of both biometric techniques (physical and behavioral) for user recognition. The verification stage determines if a person is who it claim to be. Biometric authentication based on physical features is very easy to handle and at the same time difficult to counterfeit, compared to other traditional methods such as username and password. User authentication or identification based on biometric methods is carried out in four stages [4; 5]:  
* Collection: This is used in the registration, identification and verification phases, when the system collects physical or behavioral data about the users who are interacting with the specific system;
* Extraction: The model or the distinct characteristics are extracted, and based on these, the profile of each user is created;
* Comparison: The created profile is compared to the one stored in the database;
* Match/mismatch: The system decides after comparison whether the features of the two profiles are similar or not. These steps are shown in Figure 1.  
Keyboard writing, as a biometric method of authentication, has been frequently used in recent years. By analyzing each user's way of writing, it was concluded that the typing rhythm often represents an eloquent model for the extraction and determination of the behavioral characteristics of each person. The input data consist of a flow of keyboard events (each key pressed represents an event) and the time taken by each of them. Each event is generated either by pressing a key or by releasing it. Most authentication techniques use either the time (in milliseconds) between two consecutive events, or the time it takes to type a group of characters (known as \"digraph time\") or an entire sequence. We propose the following aims for this research:  
* A better identification and understanding of the characteristics and requirements of each type of scenario (authentication as well as the duration of the working session) for continuous verification of identity;
* Implementation of algorithms that represent the writing behavior of student users and inherently reflect their profile;
* Development of a model for identifying users based on static behavior (the way a user types their username and password) to successfully authenticate;  
Figure 1: Identification of the user based on previous behavior. * Creation of a technique that identifies users based on dynamic behavior in order to successfully create profiles and establish the authenticity of users after a work session. This research is necessary because, due to the current situation, more schools and universities are adopting online education. In this way, teachers should be sure that the students are the correct students in the examination process. An approach that is being increasingly adopted by teachers is to connect online and via webcam to exactly see the student, but this approach is time-consuming. In this paper, we propose an option for automatic recognition of the students on the platform.