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

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 ba...

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Bibliographic Details
Published in2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE) pp. 836 - 841
Main Authors Shirani, Paria, Azgomi, Mohammad Abdollahi, Alrabaee, Saed
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2015
Subjects
Data models
Intrusion detection
Mathematical model
Predictive models
Time series analysis
Web services
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ISBN9781479958276
1479958271
ISSN0840-7789
DOI10.1109/CCECE.2015.7129383

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Summary: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.
ISBN:9781479958276
1479958271
ISSN:0840-7789
DOI:10.1109/CCECE.2015.7129383