Paper Info
Title
Anomaly-based intrusion detection in software as a service
Abstract
Anomaly-based intrusion detection systems (IDS) have the ability of detecting previously unknown attacks, which is important since new vulnerabilities and attacks are constantly appearing. Software as a service web applications are currently much targeted by attacks, so they are an obvious application for such IDSs. The paper presents a study of the use of anomaly-based IDSs with data from a production environment hosting a web application of large dimensions. It describes how challenges like processing a large number of requests and obtaining training data without attacks were solved. It also presents an evaluation comparing the accuracy obtained with the different types of models that were used to represent normal behavior.
Year
DOI
Venue
2011
10.1109/DSNW.2011.5958858
Dependable Systems and Networks Workshops
Keywords
Field
DocType
training data,obvious application,large number,large dimension,web application,different type,service web application,anomaly-based idss,new vulnerability,anomaly-based intrusion detection system,cloud computing,data model,intrusion detection,accuracy,software as a service,markov processes,web applications,data models,markov process
Data modeling,Data mining,Markov process,Computer science,Computer security,Software as a service,Anomaly-based intrusion detection system,Software,Web application,Intrusion detection system,Cloud computing
Conference
ISBN
Citations 
PageRank 
978-1-4577-0373-7
15
0.70
References 
Authors
9
2
Name
Order
Citations
PageRank
Gustavo Nascimento1150.70
Miguel Correia2753.31