Fraud entails deception in order to obtain illegal gains; thus, it is mainly evidenced within
financial institutions and is a matter of general interest. The problem is particularly complex …

Deep learning (DL), a branch of machine learning (ML), is the core technology in today's
technological advancements and innovations. Deep learning-based approaches are the …

Fraudsters are now more active in their attacks on credit card transactions than ever before.
With the advancement in data science and machine learning, various algorithms have been …

The improvement of intelligent surveillance systems is a functioning examination region. In
this specific situation, mobile furthermore, multi-useful robots are commonly received as …

Abstract In Machine Learning, the datasets used to build models are one of the main factors
limiting what these models can achieve and how good their predictive performance is …

The volume of e-commerce continues to increase year after year. Buying goods on the
internet is easy and practical, and took a huge boost during the lockdowns of the Covid …

The banking industry's metamorphosis through digitalization has unquestionably
revolutionized accessibility and convenience for customers worldwide. However, this …

This paper focuses on the problem of optimizing system utility of Machine-Learning (ML)
based systems in the presence of ML mispredictions. This is achieved via the use of self …

Fraud detection systems (FDS) mainly perform two tasks:(i) real-time detection while the
payment is being processed and (ii) posterior detection to block the card retrospectively and …

The identification of anomalous activities is a challenging and crucially important task in
sensor networks. This task is becoming increasingly complex with the increasing volume of …