Effective change detection in large repositories of unsolicited traffic

Ahmed, Ejaz, Clark, Andrew J., & Mohay, George M. (2009) Effective change detection in large repositories of unsolicited traffic. In Georgescu, Sorin, Heikkinen, Seppo, & Popescu, Manuela (Eds.) The Proceeding of the Fourth International Conference on Internet Monitoring and Protection, 24-28 May, 2009, Venice/Mestre, Italy.

View at publisher


When monitoring unsolicited network traffic automated detection and characterization of abrupt changes in the traffic's statistical properties is important. These abrupt changes can either be due to a single or multiple anomalous activities taking place at the same time. The start of a new anomalous activity while another anomalous activity is in operation will result in a new change nested within the previous change. Although detection of abrupt changes to identify malicious activities has received considerable attention in the past, automated detection of nested changes has not been addressed. In this paper a dynamic sliding window cumulative sum (CUSUM) algorithm is proposed to automatically identify these nested changes. The novelty of the proposed technique lies in its ability to automatically detect nested changes, without which interesting activities may go undetected, and its effectiveness in identifying both the start and the end of the individual changes. Using an analysis of real network traces, we show that the identified nested changes were indeed due to distinct malicious behaviours taking place in parallel.

Impact and interest:

12 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

169 since deposited on 10 Jun 2009
11 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 20881
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: internet monitoring, change point detection, darknet, intrusion detection
DOI: 10.1109/ICIMP.2009.8
ISBN: 9780769536125
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > COMPUTER SOFTWARE (080300) > Computer System Security (080303)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Institutes > Information Security Institute
Copyright Owner: Copyright 2009 IEEE Computer Society
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 10 Jun 2009 04:00
Last Modified: 29 Feb 2012 13:55

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page