1. Behavioral biometrics to detect fake expert profiles during negotiation.
- Author
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Nawal, Sad-Houari, Noria, Taghezout, and Abdelkader, Idris-Khodja Mohammed
- Subjects
MACHINE learning ,IDENTITY theft ,MACHINE dynamics ,RANDOM forest algorithms ,FRAUD - Abstract
Faced with the terrible spread of electronic attacks and intrusions, which tend to increase, securing computer systems has become an urgent necessity for enterprises. In this work, we are interested in a very specific security problem, which is the identity theft of business experts that causes major problems for the company, such as loss of money, fraud, information leakage, customer distrust of using the enterprise's services, etc. The implementation of an implicit authentication system based on the study of the expert behavior is a very effective way to fight this problem. The objective of this work is to propose a system dedicated to business experts, which will be able to detect impostors and false profiles during the authentication phase and during the negotiation phase in a continuous manner. The proposed system relies on machine learning algorithms, behavioral authentication, the keystroke dynamics of real experts and their behaviors during the negotiation phase, as well as their ways of interacting with the application, in order to prevent imposters to infiltrate the system by trying to login with the account of a real expert. So, we followed the following steps: Data acquisition, Criteria extraction, Model creation and Storage. We Have used three machine learning algorithms, which are: K Nearest Neighbor, Random Forest and Logistic Regression. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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