| Feature engineering strategies for credit card fraud detection AC Bahnsen, D Aouada, A Stojanovic, B Ottersten Expert Systems with Applications 51, 134-142, 2016 | 406 | 2016 |
| Example-dependent cost-sensitive decision trees AC Bahnsen, D Aouada, B Ottersten Expert Systems with Applications 42 (19), 6609-6619, 2015 | 268 | 2015 |
| Classifying Phishing URLs Using Recurrent Neural Networks AC Bahnsen, EC Bohorquez, S Villegas, J Vargas, FA González Electronic Crime Research (eCrime), 2017 APWG Symposium on, 2017 | 247 | 2017 |
| Cost sensitive credit card fraud detection using Bayes minimum risk AC Bahnsen, A Stojanovic, D Aouada, B Ottersten 2013 12th international conference on machine learning and applications 1 …, 2013 | 213 | 2013 |
| Example-Dependent Cost-Sensitive Logistic Regression for Credit Scoring A Correa Bahnsen, D Aouada, B Ottersten International Conference on Machine Learning and Applications, 7, 2014 | 152* | 2014 |
| Improving Credit Card Fraud Detection with Calibrated Probabilities AC Bahnsen, A Stojanovic, D Aouada, B Ottersten Proceedings of the fourteenth SIAM International Conference on Data Mining …, 2014 | 105 | 2014 |
| DeepPhish: Simulating Malicious AI AC Bahnsen, I Torroledo, LD Camacho, S Villegas Electronic Crime Research (eCrime), 2018 APWG Symposium on, 2018 | 82 | 2018 |
| Hunting malicious TLS certificates with deep neural networks I Torroledo, LD Camacho, AC Bahnsen Proceedings of the 11th ACM workshop on Artificial Intelligence and Security …, 2018 | 71 | 2018 |
| A novel cost-sensitive framework for customer churn predictive modeling A Correa Bahnsen, D Aouada, B Ottersten Decision Analytics, 2015 | 68 | 2015 |
| Detecting credit card fraud using periodic features AC Bahnsen, D Aouada, A Stojanovic, B Ottersten 2015 IEEE 14th international conference on machine learning and applications …, 2015 | 50 | 2015 |
| Super-app behavioral patterns in credit risk models: Financial, statistical and regulatory implications L Roa, A Correa-Bahnsen, G Suarez, F Cortés-Tejada, MA Luque, ... Expert Systems with Applications 169, 114486, 2021 | 44 | 2021 |
| Evolutionary algorithms for selecting the architecture of a MLP neural network: A credit scoring case AC Bahnsen, AM Gonzalez 2011 IEEE 11th International Conference on Data Mining Workshops, 725-732, 2011 | 37 | 2011 |
| Knowing your enemies: Leveraging data analysis to expose phishing patterns against a major US financial institution J Vargas, AC Bahnsen, S Villegas, D Ingevaldson 2016 APWG Symposium on Electronic Crime Research (eCrime), 1-10, 2016 | 27 | 2016 |
| Genetic algorithm optimization for selecting the best architecture of a multi-layer perceptron neural network: a credit scoring case A Correa, A Gonzalez, C Ladino SAS Global Forum, 2011 | 27 | 2011 |
| Phishing detection enhanced through machine learning techniques AC Bahnsen, IDT Pena, LDC Gonzalez, SV Piedrahita US Patent 10,944,789, 2021 | 23 | 2021 |
| Fraud Detection by Stacking Cost-Sensitive Decision Trees A Correa Bahnsen, S Villegas, D Aouada, B Ottersten Data Science for Cyber-Security (DSCS), London 25-27 September, 2017 | 20* | 2017 |
| Risk-based static authentication in web applications with behavioral biometrics and session context analytics J Solano, L Camacho, A Correa, C Deiro, J Vargas, M Ochoa Applied Cryptography and Network Security Workshops: ACNS 2019 Satellite …, 2019 | 18 | 2019 |
| Supporting Financial Inclusion with Graph Machine Learning and Super-App Alternative Data L Roa, A Rodríguez-Rey, A Correa-Bahnsen, C Valencia Intelligent Systems Conference, 2021 | 16 | 2021 |
| Combining behavioral biometrics and session context analytics to enhance risk-based static authentication in web applications J Solano, L Camacho, A Correa, C Deiro, J Vargas, M Ochoa International Journal of Information Security 20 (2), 181-197, 2021 | 14 | 2021 |
| Relational Graph Neural Networks for Fraud Detection in a Super-App Environment JD Acevedo-Viloria, L Roa, S Adeshina, CC Olazo, A Rodríguez-Rey, ... KDD Workshop on ML in Finance, 2021 | 9 | 2021 |
Björn OtterstenProfessor, SnT,University of Luxembourg, KTH Royal Institute of Technology, Stockholm, Sweden在 uni.lu 的电子邮件经过验证
