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This paper proposes a malicious URL detection mechanism using natural language processing. We use features including word vector representation obtained ...
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This paper proposes a malicious URL detection mechanism using natural language processing. We use features including word vector representation obtained through ...
PDF | On Jan 12, 2022, Rohit Bharadwaj and others published Is this URL Safe: Detection of Malicious URLs Using Global Vector for Word Representation | Find,
With this work we show that the ability to incorporate global word co-occurrence statistics through GloVe model helps to better discriminate between malicious ...
Detecting a URL as malicious using the lexico- graphical approach is an important research problem. This paper proposes a malicious URL detection mechanism ...
Word2Vec focuses on learning word embedding. ... Is this URL Safe: Detection of Malicious URLs Using Global Vector for Word Representation. Conference Paper.
Feb 11, 2022 · Supervised machine learning algorithms, such as SVMs, can be used to detect malicious URLs by training them on a large dataset of known ...
Jan 9, 2024 · User an ML model to detect likely Malicious domains. A lot like Polymorphic malware, a lot of malwares used DAG Dynamically Generated Domains ...
Missing: Representation. | Show results with:Representation.
Oct 16, 2023 · Mondal et al. [8] introduced a framework named SeizeMaliciousURL that utilizes an ensemble classifier for identifying malicious URLs through ...
Is this URL Safe: Detection of Malicious URLs Using Global Vector for Word Representation ... Machine Learning models were developed and trained to classify and ...