Detecting Phishing URLs With Word Embedding and Deep Learning
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F23%3A50020570" target="_blank" >RIV/62690094:18450/23:50020570 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.4018/978-1-6684-7684-0.ch011" target="_blank" >http://dx.doi.org/10.4018/978-1-6684-7684-0.ch011</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.4018/978-1-6684-7684-0.ch011" target="_blank" >10.4018/978-1-6684-7684-0.ch011</a>
Alternative languages
Result language
angličtina
Original language name
Detecting Phishing URLs With Word Embedding and Deep Learning
Original language description
learning in the phishing detection domain. However, there needs to be more research on word embeddingand deep learning for malicious URL classification. Inspired to solve this problem, this chapter aims toexamine the application of word embedding and deep learning in extracting features from website URLs.To achieve this, several word embedding techniques, such as Keras, Word2Vec, GloVe, and FastText,were used to learn feature representations of webpage URLs. The obtained feature vectors were fed intoa deep-learning model based on CNN-BiGRU for extraction and classification. Two different datasetswere used to conduct numerous experiments, while various metrics were utilized to evaluate the phishingdetection model’s performance. The obtained findings indicated that when combined with deep learning,Keras outperformed other text embedding methods and achieved the best results across all evaluationmetrics on both datasets.
Czech name
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Czech description
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Classification
Type
C - Chapter in a specialist book
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
Perspectives and Considerations on the Evolution of Smart Systems
ISBN
978-1-66847-684-0
Number of pages of the result
24
Pages from-to
296-319
Number of pages of the book
419
Publisher name
IGI Global
Place of publication
Hershey
UT code for WoS chapter
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