A behavioral based detection approach for business email compromises
| dc.contributor.advisor | Ghorbani, Ali | |
| dc.contributor.author | Maleki, Nasim | |
| dc.date.accessioned | 2023-03-01T16:17:00Z | |
| dc.date.available | 2023-03-01T16:17:00Z | |
| dc.date.issued | 2019 | |
| dc.date.updated | 2023-03-01T15:01:11Z | |
| dc.description.abstract | The most recent infectious vector in email attacks is Business Email Compromise (BEC), which is an entry point for attackers to get access to an enterprise network and obtain valuable company data. According to the Symantec Internet Threat Security Report (ISTR), around 7,710 organizations are hit by a Business Email Compromise attack every month. A BEC is a type of phishing attack that criminals impersonate a person of authority in an organization (CEO) through spoofing or take-over accounts. Since spoofing techniques are detectable using SPF, DMARC, and DKIM, we proposed and implemented a behavioral-based framework for the detection of BEC when accounts or machines are compromised. This framework stops malicious emails on the sender-side because the lack of enough email of the sender on the receiver-side cannot result in a representative user-profile. Moreover, a compromised account or machine turns into a devastating weapon targeting many people. Hence it ought to be stopped from the sender-side, and the real owner should be notified of this disaster. Our framework in the experiment on Enron Dataset for all users has reached a total average of 92% and 93% for Accuracy and F1 score, respectively. | |
| dc.description.copyright | ©Nasim Maleki, 2020 | |
| dc.description.note | Electronic Only. | |
| dc.format | text/xml | |
| dc.format.extent | xii, 80 pages | |
| dc.format.medium | electronic | |
| dc.identifier.uri | https://unbscholar.lib.unb.ca/handle/1882/13294 | |
| dc.language.iso | en_CA | |
| dc.publisher | University of New Brunswick | |
| dc.rights | http://purl.org/coar/access_right/c_abf2 | |
| dc.subject.discipline | Computer Science | |
| dc.title | A behavioral based detection approach for business email compromises | |
| dc.type | master thesis | |
| thesis.degree.discipline | Computer Science | |
| thesis.degree.fullname | Master of Computer Science | |
| thesis.degree.grantor | University of New Brunswick | |
| thesis.degree.level | masters | |
| thesis.degree.name | M.C.S. |
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