Phishing e-mails are used by malicious actors with the aim of obtaining sensitive information from a victim, deceiving or blackmailing them. An inattentive or uninformed user may often fail to recognise if an e-mail is sent by an authentic sender or is a scam. We therefore sought to develop a method that can effectively and efficiently detect phishing e-mails and report them to the user. We analyse all the information available on receipt of the e-mail both statically and performing text mining on the content and subject of the e-mail. In addition to indicating weather e-mails are suspicious, the degree of accuracy with which the above statement is made is also reported, and the aspects of the e-mail that are characteristic of a phishing e-mail are highlighted. Excellent results were achieved with our methodology, reaching 99.2% accuracy.

Detecting phishing e-mails using text mining and features analysis / Franchina, L.; Ferracci, S.; Palmaro, F.. - 2940:(2021), pp. 106-119. (Intervento presentato al convegno 5th Italian Conference on Cybersecurity, ITASEC 2021 tenutosi a Online Conference).

Detecting phishing e-mails using text mining and features analysis

Ferracci S.
;
2021

Abstract

Phishing e-mails are used by malicious actors with the aim of obtaining sensitive information from a victim, deceiving or blackmailing them. An inattentive or uninformed user may often fail to recognise if an e-mail is sent by an authentic sender or is a scam. We therefore sought to develop a method that can effectively and efficiently detect phishing e-mails and report them to the user. We analyse all the information available on receipt of the e-mail both statically and performing text mining on the content and subject of the e-mail. In addition to indicating weather e-mails are suspicious, the degree of accuracy with which the above statement is made is also reported, and the aspects of the e-mail that are characteristic of a phishing e-mail are highlighted. Excellent results were achieved with our methodology, reaching 99.2% accuracy.
2021
5th Italian Conference on Cybersecurity, ITASEC 2021
Classification; Cyber-security; Phishing; Software security; Static analysis; Text mining
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Detecting phishing e-mails using text mining and features analysis / Franchina, L.; Ferracci, S.; Palmaro, F.. - 2940:(2021), pp. 106-119. (Intervento presentato al convegno 5th Italian Conference on Cybersecurity, ITASEC 2021 tenutosi a Online Conference).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1614953
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