Deep learning to combat phishing

Author:

Maurya Swati1,Jain Anurag1

Affiliation:

1. University School of Information, Communication and Technology, Guru Gobind Singh Indraprastha University, Dwarka, New Delhi 110078, India

Publisher

Informa UK Limited

Reference19 articles.

1. Review of cyber security threats and proposed trustworthy memory acquisition mechanism

2. ‘Changing Trend in Network Security Measures: A Review’

3. Browser Extension based Hybrid Anti-Phishing Framework using Feature Selection

4. Internet filtering in china

5. zvelo (2019). Single-Use Phishing URLs Drive the Need for Zero-Second Detections. [online] zvelo. Available at: https://zvelo.com/single-use-phishing-urls-need-zero-second-detection/ [Accessed 2 October 2019].

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1. Overview of Social Engineering Protection and Prevention Methods;Lecture Notes in Computer Science;2024

2. Deep learning techniques to detect cybersecurity attacks: a systematic mapping study;Empirical Software Engineering;2023-05

3. Detecting Phishing Domains Using Machine Learning;Applied Sciences;2023-04-07

4. A comprehensive study on prevalence of cyberbullying and its impact on youths and adults;Journal of Statistics and Management Systems;2023

5. Prevention of Phishing attacks using AI Algorithm;2022 2nd Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology (ODICON);2022-11-11

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