A unifying review of deep and shallow anomaly detection
Deep learning approaches to anomaly detection (AD) have recently improved the state of
the art in detection performance on complex data sets, such as large collections of images or …
the art in detection performance on complex data sets, such as large collections of images or …
Deep learning for anomaly detection: A review
Anomaly detection, aka outlier detection or novelty detection, has been a lasting yet active
research area in various research communities for several decades. There are still some …
research area in various research communities for several decades. There are still some …
A neural network ensemble with feature engineering for improved credit card fraud detection
Recent advancements in electronic commerce and communication systems have
significantly increased the use of credit cards for both online and regular transactions …
significantly increased the use of credit cards for both online and regular transactions …
[HTML][HTML] Credit card fraud detection in the era of disruptive technologies: A systematic review
Credit card fraud is becoming a serious and growing problem as a result of the emergence
of innovative technologies and communication methods, such as contactless payment. In …
of innovative technologies and communication methods, such as contactless payment. In …
An intelligent approach to credit card fraud detection using an optimized light gradient boosting machine
AA Taha, SJ Malebary - IEEE access, 2020 - ieeexplore.ieee.org
New advances in electronic commerce systems and communication technologies have
made the credit card the potentially most popular method of payment for both regular and …
made the credit card the potentially most popular method of payment for both regular and …
Combining unsupervised and supervised learning in credit card fraud detection
Supervised learning techniques are widely employed in credit card fraud detection, as they
make use of the assumption that fraudulent patterns can be learned from an analysis of past …
make use of the assumption that fraudulent patterns can be learned from an analysis of past …
[HTML][HTML] A stacking ensemble of deep learning models for IoT intrusion detection
R Lazzarini, H Tianfield, V Charissis - Knowledge-Based Systems, 2023 - Elsevier
The number of Internet of Things (IoT) devices has increased considerably in the past few
years, which resulted in an exponential growth of cyber attacks on IoT infrastructure. As a …
years, which resulted in an exponential growth of cyber attacks on IoT infrastructure. As a …
Sequence classification for credit-card fraud detection
Due to the growing volume of electronic payments, the monetary strain of credit-card fraud is
turning into a substantial challenge for financial institutions and service providers, thus …
turning into a substantial challenge for financial institutions and service providers, thus …
CATCHM: A novel network-based credit card fraud detection method using node representation learning
Advanced fraud detection systems leverage the digital traces from (credit-card) transactions
to detect fraudulent activity in future transactions. Recent research in fraud detection has …
to detect fraudulent activity in future transactions. Recent research in fraud detection has …
Meta-learning approaches for learning-to-learn in deep learning: A survey
Y Tian, X Zhao, W Huang - Neurocomputing, 2022 - Elsevier
Compared to traditional machine learning, deep learning can learn deeper abstract data
representation and understand scattered data properties. It has gained considerable …
representation and understand scattered data properties. It has gained considerable …