Detecting Financial Fraud with Hybrid Deep Learning: A Mix-of-Experts Approach to Sequential and Anomalous Patterns
Fuente:
arXiv
Saved in:
| Main Author: | Vallarino, Diego |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Starlit: Privacy-Preserving Federated Learning to Enhance Financial Fraud Detection
by: Abadi, Aydin, et al.
Published: (2024)
by: Abadi, Aydin, et al.
Published: (2024)
FraudFox: Adaptable Fraud Detection in the Real World
by: Butler, Matthew, et al.
Published: (2026)
by: Butler, Matthew, et al.
Published: (2026)
A Multi-Scale Graph Learning Framework with Temporal Consistency Constraints for Financial Fraud Detection in Transaction Networks under Non-Stationary Conditions
by: Lei, Yiming, et al.
Published: (2026)
by: Lei, Yiming, et al.
Published: (2026)
Financial Fraud Detection using Jump-Attentive Graph Neural Networks
by: Kadam, Prashank
Published: (2024)
by: Kadam, Prashank
Published: (2024)
Addressing Noise and Stochasticity in Fraud Detection for Service Networks
by: Zhang, Wenxin, et al.
Published: (2025)
by: Zhang, Wenxin, et al.
Published: (2025)
The Performance of Sequential Deep Learning Models in Detecting Phishing Websites Using Contextual Features of URLs
by: Gopali, Saroj, et al.
Published: (2024)
by: Gopali, Saroj, et al.
Published: (2024)
Semi-Supervised Supply Chain Fraud Detection with Unsupervised Pre-Filtering
by: Moradi, Fatemeh, et al.
Published: (2025)
by: Moradi, Fatemeh, et al.
Published: (2025)
Optimized Approaches to Malware Detection: A Study of Machine Learning and Deep Learning Techniques
by: Fahim, Abrar, et al.
Published: (2025)
by: Fahim, Abrar, et al.
Published: (2025)
Enhancing Cybersecurity in IoT Networks: A Deep Learning Approach to Anomaly Detection
by: Pang, Yining, et al.
Published: (2024)
by: Pang, Yining, et al.
Published: (2024)
Leakage Safe Graph Features for Interpretable Fraud Detection in Temporal Transaction Networks
by: Khaleghpour, Hamideh, et al.
Published: (2026)
by: Khaleghpour, Hamideh, et al.
Published: (2026)
Scalable and Verifiable Federated Learning for Cross-Institution Financial Fraud Detection
by: Panth, Prajwal, et al.
Published: (2026)
by: Panth, Prajwal, et al.
Published: (2026)
Detecting Credit Card Fraud via Heterogeneous Graph Neural Networks with Graph Attention
by: Sha, Qiuwu, et al.
Published: (2025)
by: Sha, Qiuwu, et al.
Published: (2025)
A Machine Learning Driven Website Platform and Browser Extension for Real-time Scoring and Fraud Detection for Website Legitimacy Verification and Consumer Protection
by: Chy, Md Kamrul Hasan, et al.
Published: (2024)
by: Chy, Md Kamrul Hasan, et al.
Published: (2024)
IntrusionX: A Hybrid Convolutional-LSTM Deep Learning Framework with Squirrel Search Optimization for Network Intrusion Detection
by: Farabi, Ahsan, et al.
Published: (2025)
by: Farabi, Ahsan, et al.
Published: (2025)
Enhancing Network Security: A Hybrid Approach for Detection and Mitigation of Distributed Denial-of-Service Attacks Using Machine Learning
by: Shohan, Nizo Jaman, et al.
Published: (2025)
by: Shohan, Nizo Jaman, et al.
Published: (2025)
Detecting Financial Bots on the Ethereum Blockchain
by: Niedermayer, Thomas, et al.
Published: (2024)
by: Niedermayer, Thomas, et al.
Published: (2024)
LMAE4Eth: Generalizable and Robust Ethereum Fraud Detection by Exploring Transaction Semantics and Masked Graph Embedding
by: Jia, Yifan, et al.
Published: (2025)
by: Jia, Yifan, et al.
Published: (2025)
Intelligent DoS and DDoS Detection: A Hybrid GRU-NTM Approach to Network Security
by: Panggabean, Caroline, et al.
Published: (2025)
by: Panggabean, Caroline, et al.
Published: (2025)
A Survey of Malware Detection Using Deep Learning
by: Bensaoud, Ahmed, et al.
Published: (2024)
by: Bensaoud, Ahmed, et al.
Published: (2024)
Ethereum Fraud Detection via Joint Transaction Language Model and Graph Representation Learning
by: Sun, Jianguo, et al.
Published: (2024)
by: Sun, Jianguo, et al.
Published: (2024)
DexRay: A Simple, yet Effective Deep Learning Approach to Android Malware Detection based on Image Representation of Bytecode
by: Daoudi, Nadia, et al.
Published: (2021)
by: Daoudi, Nadia, et al.
Published: (2021)
Hybrid Machine Learning Approach For Real-Time Malicious Url Detection Using Som-Rmo And Rbfn With Tabu Search Optimization
by: T, Swetha, et al.
Published: (2024)
by: T, Swetha, et al.
Published: (2024)
Adaptive Malware Detection using Sequential Feature Selection: A Dueling Double Deep Q-Network (D3QN) Framework for Intelligent Classification
by: Khan, Naseem, et al.
Published: (2025)
by: Khan, Naseem, et al.
Published: (2025)
Dynamic Free-Rider Detection in Federated Learning via Simulated Attack Patterns
by: Nakamura, Motoki
Published: (2026)
by: Nakamura, Motoki
Published: (2026)
EG-ConMix: An Intrusion Detection Method based on Graph Contrastive Learning
by: Wu, Lijin, et al.
Published: (2024)
by: Wu, Lijin, et al.
Published: (2024)
Locally Differentially Private Embedding Models in Distributed Fraud Prevention Systems
by: Perez, Iker, et al.
Published: (2024)
by: Perez, Iker, et al.
Published: (2024)
Vulnerability Detection in C/C++ Code with Deep Learning
by: Huang, Zhen, et al.
Published: (2024)
by: Huang, Zhen, et al.
Published: (2024)
A Privacy-Centric Approach: Scalable and Secure Federated Learning Enabled by Hybrid Homomorphic Encryption
by: Nguyen, Khoa, et al.
Published: (2025)
by: Nguyen, Khoa, et al.
Published: (2025)
PiDAn: A Coherence Optimization Approach for Backdoor Attack Detection and Mitigation in Deep Neural Networks
by: Wang, Yue, et al.
Published: (2022)
by: Wang, Yue, et al.
Published: (2022)
Detecting Compromised IoT Devices Using Autoencoders with Sequential Hypothesis Testing
by: Mainuddin, Md, et al.
Published: (2024)
by: Mainuddin, Md, et al.
Published: (2024)
Tracing the Chain: Deep Learning for Stepping-Stone Intrusion Detection
by: Mathews, Nate, et al.
Published: (2026)
by: Mathews, Nate, et al.
Published: (2026)
Advancing DDoS Attack Detection: A Synergistic Approach Using Deep Residual Neural Networks and Synthetic Oversampling
by: Alfatemi, Ali, et al.
Published: (2024)
by: Alfatemi, Ali, et al.
Published: (2024)
A Robust Adversary Detection-Deactivation Method for Metaverse-oriented Collaborative Deep Learning
by: Li, Pengfei, et al.
Published: (2023)
by: Li, Pengfei, et al.
Published: (2023)
New Machine Learning Approaches for Intrusion Detection in ADS-B
by: Ngamboé, Mikaëla, et al.
Published: (2025)
by: Ngamboé, Mikaëla, et al.
Published: (2025)
DRMD: Deep Reinforcement Learning for Malware Detection under Concept Drift
by: McFadden, Shae, et al.
Published: (2025)
by: McFadden, Shae, et al.
Published: (2025)
Deep Learning-based Embedded Intrusion Detection System for Automotive CAN
by: Khandelwal, Shashwat, et al.
Published: (2024)
by: Khandelwal, Shashwat, et al.
Published: (2024)
Deep Learning-based Anomaly Detection and Log Analysis for Computer Networks
by: Wang, Shuzhan, et al.
Published: (2024)
by: Wang, Shuzhan, et al.
Published: (2024)
Attack and Defense of Deep Learning Models in the Field of Web Attack Detection
by: Shi, Lijia, et al.
Published: (2024)
by: Shi, Lijia, et al.
Published: (2024)
Learning to Attack: Uncovering Privacy Risks in Sequential Data Releases
by: Cui, Ziyao, et al.
Published: (2025)
by: Cui, Ziyao, et al.
Published: (2025)
Anomalous Client Detection in Federated Learning
by: Thakur, Dipanwita, et al.
Published: (2024)
by: Thakur, Dipanwita, et al.
Published: (2024)
Similar Items
-
Starlit: Privacy-Preserving Federated Learning to Enhance Financial Fraud Detection
by: Abadi, Aydin, et al.
Published: (2024) -
FraudFox: Adaptable Fraud Detection in the Real World
by: Butler, Matthew, et al.
Published: (2026) -
A Multi-Scale Graph Learning Framework with Temporal Consistency Constraints for Financial Fraud Detection in Transaction Networks under Non-Stationary Conditions
by: Lei, Yiming, et al.
Published: (2026) -
Financial Fraud Detection using Jump-Attentive Graph Neural Networks
by: Kadam, Prashank
Published: (2024) -
Addressing Noise and Stochasticity in Fraud Detection for Service Networks
by: Zhang, Wenxin, et al.
Published: (2025)