Evaluation of a Graphical Attack Fingerprint Model and Comparison against the Snort IDS

Simple item page
dc.contributor.authorSaropourian, Behnaz
dc.contributor.supervisorBaniasadi, Amirali
dc.contributor.supervisorTraore, Issa
dc.date.accessioned2022-09-27T03:26:58Z
dc.date.available2022-09-27T03:26:58Z
dc.date.copyright2022en_US
dc.date.issued2022-09-26
dc.degree.departmentDepartment of Electrical and Computer Engineeringen_US
dc.degree.levelMaster of Engineering M.Eng.en_US
dc.description.abstractToday, the number of targeted attacks has increased extremely. The attacks have increased in sophistication and diversity. It is imperative to deploy effective and proactive countermeasures that can help mitigate the threats to organizations and citizens. The Activity and Event Network (AEN) is a new knowledge graph that uses graph database technology to model security relevant network data items and their relationships as they change through time and apply various threat detection techniques. The purpose of the project is to evaluate the performance of one of the AEN threat detection techniques based on graph-based attack fingerprints or signatures, and conduct a comparison with the Snort IDS, which is a popular signature-based IDS. The evaluation was conducted using the CICIDS2017 public dataset, and discussions of the strengths and limitations of the fingerprint model were conducted, paving the way for future improvements.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/14268
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectActivity and Event Network (AEN)en_US
dc.subjectSnort IDSen_US
dc.subjectCICIDS2017en_US
dc.subjectGraph-based Attack Fingerprintsen_US
dc.titleEvaluation of a Graphical Attack Fingerprint Model and Comparison against the Snort IDSen_US
dc.typeprojecten_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Saropourian_Behnaz_MEng_2022.pdf
Size:
682.22 KB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Graduate Projects (Electrical and Computer Engineering)
 
University of Victoria Libraries

We acknowledge and respect the Lək̓ʷəŋən (Songhees and Esquimalt) Peoples on whose territory the university stands, and the Lək̓ʷəŋən and W̱SÁNEĆ Peoples whose historical relationships with the land continue to this day.