A Third-Party Intelligent System for Preventing Call Phishing and Message Scams
Author:
Publisher
Springer Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-33-4370-2_37
Reference7 articles.
1. http://www.koreaherald.com/view.php?ud=20190317000115
2. http://koreajoongangdaily.joins.com/news/article/article.aspx?aid=3059014
3. https://docs.apwg.org/reports/apwg_trends_report q1_2018.pdf
4. Amro, B.: Phishing techniques in mobile devices. J. Comput. Commun. (2018)
5. Jain, A.K., Gupta, B.B.: A novel approach to protect against phishing attacks at client side using auto-updated white-list. J. Inf. Secur. (2016)
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1. Attention-Based 1D CNN-BiLSTM Hybrid Model Enhanced with FastText Word Embedding for Korean Voice Phishing Detection;Mathematics;2023-07-21
2. A Review on Nature, Cybercrime and Best Practices of Digital Footprints;2022 International Conference on Cyber Resilience (ICCR);2022-10-06
3. Real-time Korean voice phishing detection based on machine learning approaches;Journal of Ambient Intelligence and Humanized Computing;2021-11-12
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