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We introduce a state-of-the-art approach for URL categorization that leverages the power of Large Language Models (LLMs) to address the primary objectives of web content filtering: safeguarding organizations from legal and ethical risks, limiting access to high-risk or suspicious websites, and fostering a secure and professional work environment.
A framework for detection and measurement of phishing attacks
Sujata Garera, Niels Provos, Monica Chew, and Aviel D Rubin · 2007
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Web content filtering. advances in computers., 2009
F. García · 2009
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An empirical analysis of phishing blacklists
S. Sheng, B. Wardman, G. Warner, L.F. Cranor, J. Hong, and C. Zhang · 2009
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Beyond blacklists: learning to detect malicious web sites from suspicious urls
Justin Ma, Lawrence K Saul, Stefan Savage, and Geoffrey M Voelker · 2009
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Mitigate web phishing using site signatures
Chun-Ying Huang, Shang-Pin Ma, Wei-Lin Yeh, Chia-Yi Lin, and Chien-Tsung Liu · 2010
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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Fasttext.zip: Compressing text classification models
Armand Joulin, Edouard Grave, Piotr Bojanowski, Matthijs Douze, Hérve Jégou, and Tomas Mikolov · 2016
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Joshua Saxe and Konstantin Berlin · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Urlnet: Learning a url representation with deep learning for malicious url detection
Hung Le, Quang Pham, Doyen Sahoo, and Steven CH Hoi · 2018
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Adafactor: Adaptive learning rates with sublinear memory cost
Noam Shazeer and Mitchell Stern · 2018
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A novel visual similarity-based phishing detection scheme using hue information with auto updating database
Shuichiro Haruta, Fumitaka Yamazaki, Hiromu Asahina, and Iwao Sasase · 2019
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Well-read students learn better: The impact of student initialization on knowledge distillation
Iulia Turc, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Using lexical features for malicious url detection–a machine learning approach
Apoorva Joshi, Levi Lloyd, Paul Westin, and Srini Seethapathy · 2019
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Improving web content blocking with event-loop-turn granularity javascript signatures
Quan Chen, Peter Snyder, Ben Livshits, and Alexandros Kapravelos · 2020
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Texception: a character/word-level deep learning model for phishing url detection
Farid Tajaddodianfar, Jack W Stokes, and Arun Gururajan · 2020
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Training transformers for information security tasks: A case study on malicious url prediction
Ethan M Rudd and Ahmed Abdallah · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, et al · 2020
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Urltran: Improving phishing url detection using transformers
Pranav Maneriker, Jack W Stokes, Edir Garcia Lazo, Diana Carutasu, Farid Tajaddodianfar, and Arun Gururajan · 2021
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When neural networks fail to generalize? a model sensitivity perspective
J. Zhang, H. Chao, A. Dhurandhar, P. Chen, A. Tajer, Y. Xu, and P. Yan · 2022
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Detection of malicious websites using machine learning techniques
Adebayo Oshingbesan, Courage Ekoh, Chukwuemeka Okobi, Aime Munezero, and Kagame Richard · 2022
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Less is more: Robust and novel features for malicious domain detection
Chen Hajaj, Nitay Hason, and Amit Dvir · 2022
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Towards web phishing detection limitations and mitigation
Alsharif Abuadbba, Shuo Wang, Mahathir Almashor, Muhammed Ejaz Ahmed, Raj Gaire, Seyit Camtepe, and Surya Nepal · 2022
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Optimized url feature selection based on genetic-algorithm-embedded deep learning for phishing website detection
Seok-Jun Bu and Hae-Jung Kim · 2022
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Generalization in nli: Ways (not) to go beyond simple heuristics, 2021
Prajjwal Bhargava, Aleksandr Drozd, and Anna Rogers · 2021
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Evolutionary optimization of neuro-symbolic integration for phishing url detection
Kyoung-Won Park, Seok-Jun Bu, and Sung-Bae Cho · 2021
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Learning disentangled representation of web address via convolutional-recurrent triplet network for classifying phishing urls
Seok-Jun Bu and Hae-Jung Kim · 2021
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Research on malicious url detection technology based on bert model
Weiling Chang, Fei Du, and Yijing Wang · 2021
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Phishing website detection based on multi-feature stacking
Qiang Hu, Hangxia Zhou, and Qian Liu · 2021
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Detection of malicious urls through an ensemble of machine learning techniques
Shreya Venugopal, Shreya Yuvraj Panale, Manav Agarwal, Rishab Kashyap, and U Ananthanagu · 2021
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Sharif Amit Kamran, Shamik Sengupta, and Alireza Tavakkoli · 2021
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Transformers for end-to-end infosec tasks: A feasibility study
Ethan M Rudd, Mohammad Saidur Rahman, and Philip Tully · 2022
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Towards performance of nlp transformers on url-based phishing detection for mobile devices
Hossein Shirazia, Katherine Haynesb, and Indrakshi Raya · 2022
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Tcurl: Exploring hybrid transformer and convolutional neural network on phishing url detection
Chenguang Wang and Yuanyuan Chen · 2022
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Combining long-term recurrent convolutional and graph convolutional networks to detect phishing sites using url and html
Subhash Ariyadasa, Shantha Fernando, and Subha Fernando · 2022
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Phishgnn: A phishing website detection framework using graph neural networks
Tristan Bilot, Grégoire Geis, and Badis Hammi · 2022
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Effective malicious url detection by using generative adversarial networks
Jinbu Geng, Shuhao Li, Zhicheng Liu, Zhenyu Cheng, and Li Fan · 2022
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Orel Lavie, Asaf Shabtai, and Gilad Katz · 2022
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Crafting text adversarial examples to attack the deep-learning-based malicious url detection
Zuquan Peng, Yuanyuan He, Zhe Sun, Jianbing Ni, Ben Niu, and Xianjun Deng · 2022
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Phishing url detection: A network-based approach robust to evasion
Taeri Kim, Noseong Park, Jiwon Hong, and Sang-Wook Kim · 2022
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How many websites are there, 2023
2023
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Exploring the limits of transfer learning with unified model in the cybersecurity domain
Kuntal Kumar Pal, Kazuaki Kashihara, Ujjwala Anantheswaran, Kirby C Kuznia, Siddhesh Jagtap, and Chitta Baral · 2023
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