An Empirical Study on Detecting Deception and Cybercrime Using Artificial Neural Networks-Reference-Cited by-同舟云学术

An Empirical Study on Detecting Deception and Cybercrime Using Artificial Neural Networks

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2nd International Conference on Compute and Data Analysis - ICCDA 2018
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Author:

Mbaziira Alex V.¹,Murphy Diane R.¹

Affiliation:

1. Marymount University, Arlington, VA

Publisher

ACM Press

Reference23 articles.

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4. L. Firte, C. Lemnaru, and R. Potolea, "Spam detection filter using KNN algorithm and resampling," in 2010 IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), 2010, pp. 27--33.

5. L. Pearl and M. Steyvers, "Detecting authorship deception: a supervised machine learning approach using author writeprints," LLC, vol. 27, pp. 183--196, 2012.

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1. Deception detection with machine learning: A systematic review and statistical analysis;PLOS ONE;2023-02-09

2. Cyber-Crime Detection: Experimental Techniques Comparison Analysis;2022 International Visualization, Informatics and Technology Conference (IVIT);2022-11-01