Voice phishing detection technique based on minimum classification error method incorporating codec parameters
Author:
Publisher
Institution of Engineering and Technology (IET)
Subject
Electrical and Electronic Engineering,Signal Processing
Link
https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2009.0066?crawler=true&mimetype=application/pdf
Reference24 articles.
1. Discriminative Weight Training for a Statistical Model-Based Voice Activity Detection
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1. Leveraging Artifact Reputation Analysis and Contextual Sentiment Analysis for Advanced Detection of Vishing and Smishing Attacks;2023 8th International Conference on Information Technology Research (ICITR);2023-12-07
2. Voice Recognition and Document Classification-Based Data Analysis for Voice Phishing Detection;HUM-CENT COMPUT INFO;2021
3. Bypassing Detection of URL-based Phishing Attacks Using Generative Adversarial Deep Neural Networks;Proceedings of the Sixth International Workshop on Security and Privacy Analytics;2020-03-12
4. Classifier Performance Evaluation of Phishing Detection Model on Optimal Number of Clusters;SSRN Electronic Journal;2019
5. Phishing Detection Research Based on PSO-BP Neural Network;Advances in Internet, Data & Web Technologies;2018
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