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Anomaly Based Intrusion Detection and Artificial Intelligence [chapter]

Benot Morel
2011 Intrusion Detection Systems  
2 g π χχ χχ χχ χχχ = ++− (2) If one assumes that 10% i χ ≈ www.intechopen.comAnomaly Based Intrusion Detection and Artificial Intelligence www.intechopen.comIntrusion Detection  ...  In fact most of the attempts to introduce AI in intrusion detection was in the context of anomaly-based detection.  ...  Anomaly Based Intrusion Detection and Artificial Intelligence, Intrusion Detection Systems, Dr.  ... 
doi:10.5772/14103 fatcat:4hsejdvpz5aqnl3t6w2poab7h4

Host-Based Anomaly Intrusion Detection [chapter]

Jiankun Hu
2010 Handbook of Information and Communication Security  
Acknowledgements The author appreciates discussion of the new multi-detection-engine architecture with X. Yu of RMIT University, Australia, and A. Nicholson of Monash University, Australia.  ...  Related Work on HMM-Based Anomaly Intrusion Detection HMM-based anomaly intrusion detection is a very promising and popular tool. In this part, we introduce the fundamentals of HMM.  ...  of hostbased anomaly intrusion detection in the remaining parts.  ... 
doi:10.1007/978-3-642-04117-4_13 fatcat:6tbs2h6f5re2zjedwkwrqprwfq


Shruti Karde .
2016 International Journal of Research in Engineering and Technology  
Most of the research work is going on the effectiveness and exactness of the intrusion detection, but these attempts are for the detection of the intrusions at the operating system and network level only  ...  This type of challenges can affect in two ways. 1) Missing of the database with regular patterns. 2) The detection process neglects some new patterns.  ...  Anomaly and Misuse detection are the two types of intrusion detection technique.  ... 
doi:10.15623/ijret.2016.0508029 fatcat:zxajbeiuwnhvjpibh3gqa3pkce

Anomaly Intrusion Detection Based upon Anomalous Events and Soft Computing Technique

Yingbing Yu
2015 International Journal of Machine Learning and Computing  
This paper investigates a new model to more effectively detect anomaly intrusions from masqueraders.  ...  Intrusion detection systems (IDSs) attempt to identify attacks by comparing new data to predefined signatures known to be malicious (misuse IDSs) or to a model of normal behavior (anomaly-based IDSs).  ...  , resources used by user in a session and so on [3] .  ... 
doi:10.18178/ijmlc.2015.5.6.550 fatcat:pg67vchgebg7porfdywbr7toay

A Fraud Detection System Based on Anomaly Intrusion Detection Systems for E-Commerce Applications

Daniel Massa, Raul Valverde
2014 Computer and Information Science  
This paper proposes a fraud detection system that uses different anomaly detection techniques to predict computer intrusion attacks in e-commerce web applications.  ...  Some of these fraudulent transactions that are executed in e-commerce applications happen due to successful computer intrusions on these web sites.  ...  The aim of the research is to develop a Fraud Detection System based on anomaly intrusion detection.  ... 
doi:10.5539/cis.v7n2p117 fatcat:77rbudz6hfhk3lgajmjww3qjgi

Issues and Challenges in Anomaly Intrusion Detection for HTTP Web Services

Mohsen Kakavand, Norwati Mustapha, Aida Mustapha, Mohd Taufik Abdullah, Hamed Riahi
2015 Journal of Computer Science  
We seek to identify common essential methods and solutions, as well as the gaps, limitations and challenges in anomaly intrusion detection in terms of used experimental datasets, features and techniques  ...  This paper is set to address various problems in anomaly-based intrusion detection for HTTP Web services.  ...  Ethics This article is original and contains unpublished material. The corresponding author confirms that all the other authors have read and approved the manuscript. References  ... 
doi:10.3844/jcssp.2015.1041.1053 fatcat:j2avk7ael5c4hfvijbhbqb6hmu

A Comparative Study of Hidden Markov Model and Support Vector Machine in Anomaly Intrusion Detection

Ruchi Jain, Nasser S. Abouzakhar
2013 Journal of Internet Technology and Secured Transaction  
This paper aims to analyse the performance of Hidden Markov Model (HMM) and Support Vector Machine (SVM) for anomaly intrusion detection.  ...  The specific focus of this study is to investigate and identify distinguishable TCP services that comprise of both normal and abnormal types of TCP packets, using J48 decision tree algorithm.  ...  Peter lane of University of Hertfordshire with help of Weka Tools, Romil Jain of Santa Clara University with background of HMM and SVM.  ... 
doi:10.20533/jitst.2046.3723.2013.0023 fatcat:zmyeqvmgundqnpxz67wqfcqiry

Host-based Intrusion Detection Using Signature-based and AI-driven Anomaly Detection Methods

Panos Panagiotou, Notis Mengidis, Theodora Tsikrika, Stefanos Vrochidis, Ioannis Kompatsiaris
2021 Information & Security An International Journal  
Anomaly-based Intrusion Detection Systems and Signature-based Intrusion Detection Systems are two types of systems that have been proposed in the literature to detect security threats.  ...  Cyberattacks are becoming more sophisticated, posing even greater challenges to traditional intrusion detections methods.  ...  Acknowledgements This work was supported by the ECHO project which has received funding from the European Union's Horizon 2020 research and innovation programme under the grant agreement no 830943.  ... 
doi:10.11610/isij.5016 fatcat:tyfdhyipgjbildkg65wsbdfmti

An Approach to Detect Executable Content for Anomaly Based Network Intrusion Detection

Like Zhang, Gregory B. White
2007 2007 IEEE International Parallel and Distributed Processing Symposium  
In this paper, we present a new solution to identify executable content for anomaly based network intrusion detection system (NIDS) based on file byte frequency distribution.  ...  In addition to a review of the related research on malicious code identification and file type detection in section 2, we will also discuss the drawback when applying them for NIDS.  ...  If the payload is ignored as in the traditional anomaly based intrusion detection, poor ability to identify those payload associated attacks is obvious.  ... 
doi:10.1109/ipdps.2007.370614 dblp:conf/ipps/ZhangW07 fatcat:fjn5djhq4zeoxg25v6prjhhxfa

Session Viewer: Visual Exploratory Analysis of Web Session Logs

Heidi Lam, Daniel Russell, Diane Tang, Tamara Munzner
2007 2007 IEEE Symposium on Visual Analytics Science and Technology  
Large-scale session log analysis typically includes statistical methods and detailed log examinations.  ...  We therefore built Session Viewer, a visualization tool to facilitate and bridge between statistical and detailed analyses.  ...  initiation counts based on author [33] , and SnortView, which shows network-based intrusion detection system logs as a 2D time diagram [19] .  ... 
doi:10.1109/vast.2007.4389008 dblp:conf/ieeevast/LamRTM07 fatcat:ohpqldv7jzd3habpfczfo5h2ru

An Anomaly Intrusion Detection Method Based on Improved K-Means of Cloud Computing

Xinlong Zhao, Weishi Zhang
2016 2016 Sixth International Conference on Instrumentation & Measurement, Computer, Communication and Control (IMCCC)  
Moreover, the traditional network-based intrusion detection systems (IDSs) are ineffective to be deployed in cloud environments.  ...  Our approach deploys the IDS sensors in each virtual machine to create a cooperative environment for our anomaly detection engine.  ...  the intrusion detection literature.  ... 
doi:10.1109/imccc.2016.108 fatcat:jrdcmpgdnjavpnjvhzlcdpwtru

Intelligent and Improved Self-Adaptive Anomaly based Intrusion Detection System for Networks

Zouhair Chiba, Noreddine Abghour, Khalid Moussaid, Amina El omri, Rida Mohamed
2022 International Journal of Communication Networks and Information Security  
Moreover, improvement of GA through FVH and PP saves processing power and execution time. Thus, our model is very much convenient for network anomaly detection.  ...  There is a great need for an effective Network Intrusion Detection System (NIDS), which are security tools designed to interpret the intrusion attempts in incoming network traffic, thereby achieving a  ...  We would like to thank all the members of LIMSAD Laboratory of Department of Mathematics and Computer Science for their help and support.  ... 
doi:10.17762/ijcnis.v11i2.4144 fatcat:sbkeoh3w6fh6dbs3v2ttn6fane

Anomaly Intrusion Detection System Using Gaussian Mixture Model

M. Bahrololum, M. Khaleghi
2008 2008 Third International Conference on Convergence and Hybrid Information Technology  
Anomaly-based approaches in Intrusion Detection Systems have the advantage of being able to detect unknown attacks; they look for patterns that deviate from the normal behavior.  ...  Intrusion Detection Systems have been widely used to overcome security threats in computer networks and to identify unauthorized use, misuse, and abuse of computer systems.  ...  IDSs are categorized into misuse detection and anomaly detection systems [2] .  ... 
doi:10.1109/iccit.2008.17 fatcat:s566ekhbybht3pwpq62337354y

Oral Sessions

2011 International Journal of Paediatric Dentistry  
In session 1, age and diagnoses at the time of injury were unknown, in session 2, this information was given. Inter-observer agreement was calculated using Cohen's kappa.  ...  problems like dental caries, periodontal diseases, tooth anomalies, facial trauma and injury.  ...  Report: Scotland has a population of 5 million people, with a density of >1000/km 2 in the four main cities but as low as 0-9/ km 2 in northern and island regions.  ... 
doi:10.1111/j.1365-263x.2011.01137.x pmid:21672059 fatcat:yyiyms3t4nd2zh7czwusqjwb2a

Classification of Malicious Web Sessions

Katerina Goseva-Popstojanova, Goce Anastasovski, Risto Pantev
2012 2012 21st International Conference on Computer Communications and Networks (ICCCN)  
detection, and service recovery in the cyberspace.  ...  Our results show that the supervised learning methods can be used to efficiently distinguish attack sessions from vulnerability scan sessions, with very high probability of detection and very low probability  ...  Last but not least, significant amount of intrusion detection research work was based on outdated data sets such as the DARPA Intrusion Detection Data Set [8] and its derivative KDD 1999 [14] .  ... 
doi:10.1109/icccn.2012.6289291 dblp:conf/icccn/Goseva-PopstojanovaAP12 fatcat:3n4f37bi5vccnn5zcrlcyvhara
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