The number of fraud occurrences in electronic banking is rising each year. Experts in the
field of cybercrime are continuously monitoring and verifying network infrastructure and …

Insider threats pose a significant risk to organizations, necessitating robust detection
mechanisms to safeguard against potential damage. Traditional methods struggle to detect …

The integration of artificial intelligence (AI) into daily life, particularly through information
retrieval and recommender systems, has necessitated advanced user modeling and …

Despite being the most widely used authentication mechanism, password-based
authentication is not very secure, being easily guessed or brute-forced. To address this …

In a modern digital environment, there is a continual need for new and better authentication
methods, particularly in the context of Multi-Factor Authentication systems. A new …

The ability to detect the anomalous user behavior automatically and create user profiles,
storing fresh and accurate security aspect user information, is important for systems …

Mostly, security user profiles are being generated from real-time sources of users' data. User
profiles generation process involves complicated and comprehensive data analysis …

Machine learning is an extremely important technique that has become heavily used in
different types of applications such as detection systems for fraud, intrusion or fault and …

In the past few years, there has been an exponential growth in network and Internet traffic.
This trend will continue to increase due to digitalization and resulting in more …

Anomaly detection is quickly becoming a very significant tool for a variety of applications
such as intrusion detection, fraud detection, fault detection, system health monitoring, and …