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

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.

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Publication Details

Journal
Iconic Research and Engineering Journals
Published
2026-03-26
DOI
https://doi.org/10.64388/irev9i9-1715472
Primary Topic
Software System Performance and Reliability
Type
article
Field-Weighted Citation Impact
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article

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

Ujwala Sav, Shivam Gupta
Iconic Research and Engineering Journals
Software System Performance and Reliability
article

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

Ujwala Sav, Shivam Gupta
article en

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.

Iconic Research and Engineering JournalsVol. 9(9)
Openalex Percentile: Top 6%
Software System Performance and Reliability
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Anomaly Detection in E-commerce Transactions Using Hybrid Deep Learning Models — Ujwala Sav, Shivam Gupta · Iconic Research and Engineering Journals (2026) | TGRS Research Map | TGRS