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Anomaly Detection in E-commerce Transactions Using Hybrid Deep Learning Models

Year: 2026

Type: article

Abstract: As online shopping continues to explode, so do the tactics used by fraudsters.The old-school method of using "rule-based" systems essentially a rigid checklist of "if this, then that" is falling behind because modern fraud is constantly evolving.To stay ahead, we've developed a hybrid framework that acts like a digital detective, combining two powerful tools: Autoencoders and Isolation Forests.

Source: Iconic Research and Engineering Journals

DOI: 10.64388/irev9i9-1715472

Authors: Shivam Gupta, Dr. Ujwala Sav

Institutions: University of Mumbai, Vidyalankar School of Information Technology

Language: English

Topic: Anomaly Detection Techniques and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W7140884364

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