Towards Polyvalent Adversarial Attacks on URL Classification Engines
Author:
Affiliation:
1. National Institute of Information and Communications Technology, Tokyo, Japan
2. Saitama Institute of Technology, Saitama, Japan
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3488932.3527282
Reference17 articles.
1. 2022. DeepPhishFinder. https://twitter.com/DeepPhish 2022. DeepPhishFinder. https://twitter.com/DeepPhish
2. 2022. VirusTotal. https://virustotal.com/ 2022. VirusTotal. https://virustotal.com/
3. Generating Optimal Attack Paths in Generative Adversarial Phishing
4. Bypassing Detection of URL-based Phishing Attacks Using Generative Adversarial Deep Neural Networks
5. Deep abstraction and weighted feature selection for Wi-Fi impersonation detection;Erza Aminanto Muhamad;IEEE Transactions on Information Forensics and Security,2017
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