Detection of Fraudulent Sellers in Online Marketplaces using Support Vector Machine Approach
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2018 by IJETT Journal|
|Year of Publication : 2018|
|Authors : Shini Renjith
|DOI : 10.14445/22315381/IJETT-V57P210|
Shini Renjith "Detection of Fraudulent Sellers in Online Marketplaces using Support Vector Machine Approach", International Journal of Engineering Trends and Technology (IJETT), V57(1),48-53 March 2018. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
The e-commerce share in the global retail spend is showing a steady increase over the years indicating an evident shift of consumer attention from bricks and mortar to clicks in retail sector. In recent years, online marketplaces have become one of the key contributors to this growth. As the business model matures, the number and types of frauds getting reported in the area is also growing on a daily basis. Fraudulent e-commerce buyers and their transactions are being studied in detail and multiple strategies to control and prevent them are discussed. Another area of fraud happening in marketplaces are on the seller side and is called merchant fraud. Goods/services offered and sold at cheap rates, but never shipped is a simple example of this type of fraud. This paper attempts to suggest a framework to detect such fraudulent sellers with the help of machine learning techniques. The model leverages the historic data from the marketplace and detect any possible fraudulent behaviours from sellers and alert to the marketplace.
 Caldeira, Evandro, Gabriel Brandao, and Adriano CM Pereira. "Fraud Analysis and Prevention in e-Commerce Transactions." In Web Congress (LA-WEB), 2014 9th Latin American, pp. 42-49. IEEE, 2014.
 Renjith, Shini. "An Integrated Framework to Recommend Personalized Retention Actions to Control B2C E-Commerce Customer Churn." International Journal of Engineering Trends and Technology (IJETT), vol. 27, no. 3, pp. 152-157 September 2015. Seventh Sense Research Group, 2015.
 Renjith, Shini. "B2C E-Commerce Customer Churn Management: Churn Detection using Support Vector Machine and Personalized Retention using Hybrid Recommendations." International Journal on Future Revolution in Computer Science & Communication Engineering (IJFRCSCE), vol. 3, no. 11, pp. 34-39 November 2017. Auricle Technologies Pvt. Ltd, 2017.
 Raj, S. Benson Edwin, and A. Annie Portia. "Analysis on credit card fraud detection methods." In Computer, Communication and Electrical Technology (ICCCET), 2011 International Conference on, pp. 152-156. IEEE, 2011.
 Brabazon, Anthony, Jane Cahill, Peter Keenan, and Daniel Walsh. "Identifying online credit card fraud using artificial immune systems." In Evolutionary Computation (CEC), 2010 IEEE Congress on, pp. 1-7. IEEE, 2010.
 Bahnsen, Alejandro Correa, DjamilaAouada, AleksandarStojanovic, and BjörnOttersten. "Detecting Credit Card Fraud using Periodic Features." In Machine Learning and Applications (ICMLA), 2015 IEEE 14th International Conference on, pp. 208-213. IEEE, 2015.
 Lei, Liang. "Card fraud detection by inductive learning and evolutionary algorithm." In Genetic and Evolutionary Computing (ICGEC), 2012 Sixth International Conference on, pp. 384-388. IEEE, 2012.
 Srivastava, Abhinav, AmlanKundu, ShamikSural, and Arun Majumdar. "Credit card fraud detection using hidden Markov model." IEEE Transactions on dependable and secure computing, vol. 5, no. 1 (2008): 37-48. IEEE, 2008.
 Guo, Tao, and Gui-Yang Li. "Neural data mining for credit card fraud detection." In Machine Learning and Cybernetics, 2008 International Conference on, vol. 7, pp. 3630-3634. IEEE, 2008.
 Elfahmi, Muhammad HaritsShalahuddinAdilHaqqi, and GustiAyuPutriSaptawati. "Feedback fraud detection on online marketplace system based on fusion approach." In Data and Software Engineering (ICoDSE), 2015 International Conference on, pp. 108-113. IEEE, 2015.
 Bahnsen, Alejandro Correa, AleksandarStojanovic, DjamilaAouada, and Bjorn Ottersten. "Cost sensitive credit card fraud detection using Bayes minimum risk." In Machine Learning and Applications (ICMLA), 2013 12th International Conference on, vol. 1, pp. 333-338. IEEE, 2013.
 Maranzato, Rafael, MardenNeubert, Adriano M. Pereira, and Alair Pereira do Lago. "Feature extraction for fraud detection in electronic marketplaces." In Web Congress, 2009. LAWEB` 09. Latin American, pp. 185-192. IEEE, 2009.
 Banerjee, Siddhartha, Zhengyuan Zhou, and Ramesh Johari. "The importance of exploration in online marketplaces." In Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on, pp. 3499-3504. IEEE, 2014.
 Cortes, Corinna, and Vladimir Vapnik. "Support-vector networks." Machine learning, vol. 20, no. 3 (1995): 273-297.
 LeCun, Yann, L. D. Jackel, Léon Bottou, Corinna Cortes, John S. Denker, Harris Drucker, Isabelle Guyon, Urs A. Muller, Eduard Sackinger, Patrice Simard and Vladimir Vapnik. "Learning algorithms for classification: A comparison on handwritten digit recognition." Neural International Journal of Engineering Trends and Technology (IJETT) – Volume 57 Number 1 - March2018 ISSN: 2231-5381 http://www.ijettjournal.org Page 53 networks: the statistical mechanics perspective 261 (1995): 276.
 Osuna, Edgar, Robert Freund, and Federico Girosit. "Training support vector machines: an application to face detection." In Computer vision and pattern recognition, 1997. Proceedings, 1997 IEEE computer society conference on, pp. 130-136. IEEE, 1997.
 Oren, Michael, Constantine Papageorgiou, Pawan Sinha, Edgar Osuna, and TomasoPoggio. "Pedestrian detection using wavelet templates." In Computer Vision and Pattern Recognition, 1997. Proceedings, 1997 IEEE Computer Society Conference on, pp. 193-199. IEEE, 1997.
 Joachims, Thorsten. "Text categorization with support vector machines: Learning with many relevant features." Machine learning: ECML-98 (1998): 137-142.
 Singh, Gajendra, Ravindra Gupta, Ashish Rastogi, Mahiraj DS Chandel, and A. Riyaz. "A machine learning approach for detection of fraud based on svm." International Journal of Scientific Engineering & Technology 1, no. 3 (2012).
 Vapnik, Vladimir Naumovich, and Samuel Kotz. Estimation of dependences based on empirical data. Vol. 40. New York: Springer-Verlag, 1982.
 Osuna, Edgar, Robert Freund, and Federico Girosi. "An improved training algorithm for support vector machines." In Neural Networks for Signal Processing  VII. Proceedings of the 1997 IEEE Workshop, pp. 276-285. IEEE, 1997.
 Platt, John. "Sequential minimal optimization: A fast algorithm for training support vector machines." (1998).
 Chang, Chih-Chung, and Chih-Jen Lin. "LIBSVM: a library for support vector machines." ACM transactions on intelligent systems and technology (TIST) 2, no. 3 (2011): 27.
Online Marketplace, Fraud Detection, Machine Learning, Supervised Learning, Support Vector Machines.