Peer-reviewed open-access journal
published since 1998 by Procon Ltd.

Volume

ISIJ 53: Enhanced Collaboration for Cyber Security and Resilience

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Reviewed article

A Novel Approach for Analysing and Predicting the Online Money Transactions Using Machine Learning Auto Encoders

Alamanda Amulya, Ragu Sai, Yaga Srivalli, Kunche Kavya, Kalidindi Jyothika

How to cite:

Alamanda Amulya, Ragu Sai, Yaga Srivalli, Kunche Kavya, Kalidindi Jyothika

"A Novel Approach for Analysing and Predicting the Online Money Transactions Using Machine Learning Auto Encoders"

Journal of Engineering Sciences,

13,

(2022):

Authors:

Alamanda Amulya, Ragu Sai, Yaga Srivalli, Kunche Kavya, Kalidindi Jyothika

Source:

Journal of Engineering Sciences,

Volume: 13,

(2022)

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References

Vladimir Zaslavsky, Anna Strizhak

"Credit Card Fraud Detection Using Self-Organizing Maps."

Information & Security: An International Journal

(2006):

48-63.

Field of application

Concepts and Implementation

Policy, strategy and doctrine

Technologies

C4ISR

Architectures

Modelling and Simulation

OR & Systems Analysis

Cryptography

Data mining

Deep Learning & AI

Emerging Technologies

ISIJ 53: Enhanced Collaboration for Cyber Security and Resilience

A Novel Approach for Analysing and Predicting the Online Money Transactions Using Machine Learning Auto Encoders

The C-factor in the Cybersecurity Equation: The Importance of Student Cybersecurity Competitions

On Inequalities Bounding Imprecision and Nonspecificity Measures of Uncertainty

On the Effectiveness of Measures of Uncertainty of Basic Belief Assignments

Blockchain in Agriculture

A Novel Approach for Analysing and Predicting the Online Money Transactions Using Machine Learning Auto Encoders

Authors:

Source:

Field of application

Concepts and Implementation

Technologies