"Kn0w Thy Doma1n Name"
Author:
Affiliation:
1. Colorado State University, Fort Collins, CO, USA
2. Colorado State University, Fort Collisn, CO, USA
Funder
SecureNoK
Air Force Research Laboratory
National Science Foundation
Furuno Electric Company,
CableLabs
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3205977.3205992
Reference22 articles.
1. Phishing detection: A recent intelligent machine learning comparison based on models content and features
2. Using supervised machine learning algorithms to detect suspicious URLs in online social networks
3. Ram B. Basnet Srinivas Mukkamala and Andrew H. Sung. 2008. Detection of Phishing Attacks: A Machine Learning Approach. Soft Computing Applications in Industry. Studies in Fuzziness and Soft Computing. Vol. Vol. 226. Springer 373--383. Ram B. Basnet Srinivas Mukkamala and Andrew H. Sung. 2008. Detection of Phishing Attacks: A Machine Learning Approach. Soft Computing Applications in Industry. Studies in Fuzziness and Soft Computing. Vol. Vol. 226. Springer 373--383.
4. Tracking Phishing Attacks Over Time
5. Systematization of Knowledge (SoK): A Systematic Review of Software-Based Web Phishing Detection
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3. Mitigating Bias in Machine Learning Models for Phishing Webpage Detection;2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS);2024-01-03
4. Detection of Turkish Fraudulent Domain Names to Proactively Prevent Phishing Attacks Using A Character-Level Convolutional Neural Network;2023 Innovations in Intelligent Systems and Applications Conference (ASYU);2023-10-11
5. Life-long phishing attack detection using continual learning;Scientific Reports;2023-07-17
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