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  4. RoBERTa for URL Classification: Enhancing Web Security and Content Filtering
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RoBERTa for URL Classification: Enhancing Web Security and Content Filtering

Journal
2023 31st Telecommunications Forum (TELFOR)
Date Issued
2023-11-21
Author(s)
Ilievska, Joana
Mihajloska Trpcheska Hristina
Dobreva, Jovana
DOI
10.1109/telfor59449.2023.10372764
Abstract
The rising occurrence of malicious URLs on the internet is a major concern for users and their devices. To combat this problem, there is a need to develop effective methods to protect against these threats. The use of artificial intelligence (AI) presents an opportunity to leverage this technology to tackle this issue. This study proposes a URL classification model that uses RoBERTa transformer, an AI-based natural language processing technique, to classify URLs based on their intent. The model’s performance has been evaluated using various metrics, showcasing the potential of AI to assist in the creation of robust web security and online content filtering tools.
Subjects

URL classification

malicious URLs

web security

online content filter...

RoBERTa transformer

machine learning

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