Detection of Phishing Emails

Bedrane, Ilhem; Boumahdi, Faima ( Promotrice)

dc.contributor.author	Bedrane, Ilhem
dc.contributor.author	Boumahdi, Faima ( Promotrice)
dc.date.accessioned	2022-12-13T12:26:58Z
dc.date.available	2022-12-13T12:26:58Z
dc.date.issued	2022
dc.identifier.uri	https://di.univ-blida.dz/jspui/handle/123456789/20465
dc.description	ill., Bibliogr. Cote: ma-004-881	fr_FR
dc.description.abstract	In recent years, cyber criminals have successfully invaded many important information systems by using phishing mail, causing huge losses. The detection of phishing mail from big email data has been paid public attention. However, the camouflage technology of phishing mail is becoming more and more complex, and the existing detection methods are unable to confront with the increasingly complex deception methods and the growing number of emails. In this paper we transformed the probleme from classification of emails into similarity detection between two emails in order to classify them into 4 mains classes “ Normal, Harrassment , suspicious and fraudulent” to solve this probleme we used Siamese Neural networks which gave us an accuracy of 95.13%. Key words : NLP, Siamese network, deep learning, phishing attacks, phishing detection, similarity learning.	fr_FR
dc.language.iso	en	fr_FR
dc.publisher	Université Blida 1	fr_FR
dc.subject	NLP	fr_FR
dc.subject	Siamese network	fr_FR
dc.subject	deep learning	fr_FR
dc.subject	phishing attacks	fr_FR
dc.subject	phishing detection	fr_FR
dc.subject	similarity learning	fr_FR
dc.title	Detection of Phishing Emails	fr_FR
dc.type	Thesis	fr_FR