Matches in SemOpenAlex for { <https://semopenalex.org/work/W2797698575> ?p ?o ?g. }
Showing items 1 to 86 of
86
with 100 items per page.
- W2797698575 abstract "Phishing is referred as an attempt to obtain sensitive information, such as usernames, passwords, and credit card details (and, indirectly, money), for malicious reasons, by disguising as a trustworthy entity in an electronic communication [1]. Hackers and malicious users, often use Emails as phishing tools to obtain the personal data of legitimate users, by sending Emails with authentic identities, legitimate content, but also with malicious URL, which help them to steal consumer's data. The high dimensional data in phishing context contains large number of redundant features that significantly elevate the classification error. Additionally, the time required to perform classification increases with the number of features. So extracting complex Features from phishing Emails requires us to determine which Features are relevant and fundamental in phishing detection. The dominant approaches in phishing are based on machine learning techniques; these rely on manual feature engineering, which is time consuming. On the other hand, deep learning is a promising alternative to traditional methods. The main idea of deep learning techniques is to learn complex features extracted from data with minimum external contribution [2]. In this paper, we propose new phishing detection and prevention approach, based first on our previous spam filter [3] to classify textual content of Email. Secondly it's based on Autoencoder and on Denoising Autoencoder (DAE), to extract relevant and robust features set of URL (to which the website is actually directed), therefore the features space could be reduced considerably, and thus decreasing the phishing detection time." @default.
- W2797698575 created "2018-04-24" @default.
- W2797698575 creator A5024601930 @default.
- W2797698575 creator A5080672980 @default.
- W2797698575 creator A5088931376 @default.
- W2797698575 date "2017-12-20" @default.
- W2797698575 modified "2023-09-23" @default.
- W2797698575 title "Advanced Phishing Filter Using Autoencoder and Denoising Autoencoder" @default.
- W2797698575 cites W1880332085 @default.
- W2797698575 cites W1964126497 @default.
- W2797698575 cites W2023917709 @default.
- W2797698575 cites W2025768430 @default.
- W2797698575 cites W2061519013 @default.
- W2797698575 cites W2093108064 @default.
- W2797698575 cites W2114191341 @default.
- W2797698575 cites W2134750673 @default.
- W2797698575 cites W2139565456 @default.
- W2797698575 cites W2148244131 @default.
- W2797698575 cites W2242427765 @default.
- W2797698575 cites W2601590138 @default.
- W2797698575 cites W2735268837 @default.
- W2797698575 cites W4231109964 @default.
- W2797698575 doi "https://doi.org/10.1145/3175684.3175690" @default.
- W2797698575 hasPublicationYear "2017" @default.
- W2797698575 type Work @default.
- W2797698575 sameAs 2797698575 @default.
- W2797698575 citedByCount "6" @default.
- W2797698575 countsByYear W27976985752019 @default.
- W2797698575 countsByYear W27976985752020 @default.
- W2797698575 countsByYear W27976985752021 @default.
- W2797698575 countsByYear W27976985752022 @default.
- W2797698575 crossrefType "proceedings-article" @default.
- W2797698575 hasAuthorship W2797698575A5024601930 @default.
- W2797698575 hasAuthorship W2797698575A5080672980 @default.
- W2797698575 hasAuthorship W2797698575A5088931376 @default.
- W2797698575 hasConcept C101738243 @default.
- W2797698575 hasConcept C106131492 @default.
- W2797698575 hasConcept C108583219 @default.
- W2797698575 hasConcept C109297577 @default.
- W2797698575 hasConcept C110875604 @default.
- W2797698575 hasConcept C119857082 @default.
- W2797698575 hasConcept C124101348 @default.
- W2797698575 hasConcept C136764020 @default.
- W2797698575 hasConcept C151730666 @default.
- W2797698575 hasConcept C154945302 @default.
- W2797698575 hasConcept C2779343474 @default.
- W2797698575 hasConcept C31972630 @default.
- W2797698575 hasConcept C38652104 @default.
- W2797698575 hasConcept C41008148 @default.
- W2797698575 hasConcept C52622490 @default.
- W2797698575 hasConcept C83860907 @default.
- W2797698575 hasConcept C86803240 @default.
- W2797698575 hasConceptScore W2797698575C101738243 @default.
- W2797698575 hasConceptScore W2797698575C106131492 @default.
- W2797698575 hasConceptScore W2797698575C108583219 @default.
- W2797698575 hasConceptScore W2797698575C109297577 @default.
- W2797698575 hasConceptScore W2797698575C110875604 @default.
- W2797698575 hasConceptScore W2797698575C119857082 @default.
- W2797698575 hasConceptScore W2797698575C124101348 @default.
- W2797698575 hasConceptScore W2797698575C136764020 @default.
- W2797698575 hasConceptScore W2797698575C151730666 @default.
- W2797698575 hasConceptScore W2797698575C154945302 @default.
- W2797698575 hasConceptScore W2797698575C2779343474 @default.
- W2797698575 hasConceptScore W2797698575C31972630 @default.
- W2797698575 hasConceptScore W2797698575C38652104 @default.
- W2797698575 hasConceptScore W2797698575C41008148 @default.
- W2797698575 hasConceptScore W2797698575C52622490 @default.
- W2797698575 hasConceptScore W2797698575C83860907 @default.
- W2797698575 hasConceptScore W2797698575C86803240 @default.
- W2797698575 hasLocation W27976985751 @default.
- W2797698575 hasOpenAccess W2797698575 @default.
- W2797698575 hasPrimaryLocation W27976985751 @default.
- W2797698575 hasRelatedWork W2567271240 @default.
- W2797698575 hasRelatedWork W2788487394 @default.
- W2797698575 hasRelatedWork W2922457425 @default.
- W2797698575 hasRelatedWork W2946016983 @default.
- W2797698575 hasRelatedWork W3044458868 @default.
- W2797698575 hasRelatedWork W4210666970 @default.
- W2797698575 hasRelatedWork W4213225422 @default.
- W2797698575 hasRelatedWork W4250304930 @default.
- W2797698575 hasRelatedWork W4289656111 @default.
- W2797698575 hasRelatedWork W4307326401 @default.
- W2797698575 isParatext "false" @default.
- W2797698575 isRetracted "false" @default.
- W2797698575 magId "2797698575" @default.
- W2797698575 workType "article" @default.