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What is Malicious URL Classification System Analysis about?
The existing system for malicious URL classification employs traditional machine learning algorithms such as SVMs, RFs, DTs, and KNNs, achieving high F1 scores but facing limitations in capturing sequential patterns and real-time deployment. It processes a dataset of 650,000 URLs, utilizing instance selection methods to enhance efficiency, yet struggles with class imbalance and computational inefficiencies. The proposed CNN+LSTM framework aims to address these shortcomings by incorporating advanced modeling
- Author
- yaskalai1602
- Language
- EN