A method for intrusion detection in web services based on time series

Paria Shirani, Mohammad Abdollahi Azgomi, Saed Alrabaee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

A prevalent issue in today's society that has attracted much attention is anomaly detection in time series. Service-oriented architecture (SOA) and web services are considered as one of the most important technologies. In this paper, we propose a model for intrusion detection in web services based on the autoregressive integrated moving average (ARIMA). First, we apply the ARIMA model to the training data. Second, we forecast their next behavior within a specific confidence interval. Third, we examine the testing data; if any instance falls out of the range of the confidence interval, it might be an anomaly, and the system will notify the administrator. We present experiments and results obtained using real world data.

Original languageEnglish
Title of host publication2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering, CCECE 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages836-841
Number of pages6
EditionJune
ISBN (Electronic)9781479958276
DOIs
Publication statusPublished - Jun 19 2015
Externally publishedYes
Event2015 28th IEEE Canadian Conference on Electrical and Computer Engineering, CCECE 2015 - Halifax, Canada
Duration: May 3 2015May 6 2015

Publication series

NameCanadian Conference on Electrical and Computer Engineering
NumberJune
Volume2015-June
ISSN (Print)0840-7789

Conference

Conference2015 28th IEEE Canadian Conference on Electrical and Computer Engineering, CCECE 2015
Country/TerritoryCanada
CityHalifax
Period5/3/155/6/15

ASJC Scopus subject areas

  • Hardware and Architecture
  • Electrical and Electronic Engineering

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