liu.seSök publikationer i DiVA
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
A Performance Analysis of Intrusion Detection with Snort and Security Information Management
Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik.
2021 (Engelska)Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)Alternativ titel
En Prestandaanalys av Intrångsdetektering med Snort och Hantering av Säkerhetsinformation (Svenska)
Abstract [en]

Network intrusion detection systems (NIDSs) are a major component in cybersecurity and can be implemented with open-source software. Active communities and researchers continue to improve projects and rulesets used for detecting threats to keep up with the rapid development of the internet. With the combination of security information management, automated threat detection updates and widely used software, the NIDS security can be maximized. However, it is not clear how different combinations of software and basic settings affect network performance.

The main purpose in this thesis was to find out how multithreading, standard ruleset configurations and near real-time data shipping affect Snort IDS’ online and offline performance. Investigations and results were designed to guide researchers or companies to enable maximum security with minimum impact on connectivity. Software used in performance testing was limited to Snort 2.9.17.1-WIN64 (IDS), Snort 3.1.0.0 (IDS), PulledPork (rule management) and Open Distro for Elasticsearch (information management). To increase the replicability of this study, the experimentation method was used, and network traffic generation was limited to 1.0 Gbit/s hardware. Offline performance was tested with traffic recorded from a webserver during February 2021 to increase the validity of test results, but detection of attacks was not the focus.

Through experimentation it was found that multithreading enabled 68-74% less runtime for offline analysis on an octa-thread system. On the same system, Snort’s drop rate was reduced from 9.0% to 1.1% by configuring multiple packet threads for 1.0 Gbit/s traffic. Secondly, Snort Community and Proofpoint ET Open rulesets showed approximately 1% and 31% dropped packets, respectively. Finally, enabling data shipping services to integrate Snort with Open Distro for Elasticsearch (ODFE) did not have any negative impact on throughput, network delay or Snort’s drop rate. However, the usability of ODFE needs further investigation.

In conclusion, Snort 3 multithreading enabled major performance benefits but not all open-source rules were available. In future work, the shared security information management solution could be expanded to include multiple Snort sensors, triggers, alerting (email) and suggested actions for detected threats.

Ort, förlag, år, upplaga, sidor
2021. , s. 84
Nyckelord [en]
Snort, Snort 3, PulledPork, IDS, Open Distro for Elasticsearch, ODFE, SIM, SIEM, ET Open, D-ITG
Nationell ämneskategori
Data- och informationsvetenskap
Identifikatorer
URN: urn:nbn:se:liu:diva-177602ISRN: LIU-IDA/LITH-EX-A--21/068--SEOAI: oai:DiVA.org:liu-177602DiVA, id: diva2:1575399
Externt samarbete
MindRoad AB
Ämne / kurs
Datateknik
Presentation
2021-06-21, Linköping, 14:00 (Engelska)
Handledare
Examinatorer
Tillgänglig från: 2021-06-30 Skapad: 2021-06-29 Senast uppdaterad: 2021-06-30Bibliografiskt granskad

Open Access i DiVA

fulltext(2904 kB)2735 nedladdningar
Filinformation
Filnamn FULLTEXT01.pdfFilstorlek 2904 kBChecksumma SHA-512
72d6052cc4068975f64cc4c68871965f5374ed4b9a809aa7a715ed05e981a717b5fead531b0d9630ad43163e0fbc76ec0e8fbeab4da30d47d79b797c5c40bb56
Typ fulltextMimetyp application/pdf

Av organisationen
Databas och informationsteknik
Data- och informationsvetenskap

Sök vidare utanför DiVA

GoogleGoogle Scholar
Totalt: 2735 nedladdningar
Antalet nedladdningar är summan av nedladdningar för alla fulltexter. Det kan inkludera t.ex tidigare versioner som nu inte längre är tillgängliga.

urn-nbn

Altmetricpoäng

urn-nbn
Totalt: 2379 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf