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On a pattern-oriented model for intrusion detection

Shiuh-Pyng Shieh, V.D. Gligor
1997 IEEE Transactions on Knowledge and Data Engineering  
We motivate the need for pattern-oriented intrusion detection, and present a model that tracks both data and privilege flows within secure systems to detect context-dependent intrusions caused by operational  ...  As with all pattern-oriented models, this model cannot be used to detect new, unanticipated intrusion patterns that could be detected by statistical models.  ...  Some of the results presented in this paper appeared in the Proceedings of the 1991 IEEE Symposium on Research in Security and Privacy. The authors are grateful to Prof.  ... 
doi:10.1109/69.617059 fatcat:zf24phj7lbhghbvbz75ycs7m5e

Intrusion Detection Using Fuzzy Meta-Heuristic Approaches

Bachir Bahamida, Dalila Boughaci
2014 International Journal of Applied Metaheuristic Computing  
The second one is a fuzzy tabu search (FTS) and the third one is a fuzzy deferential evolution (FDE). These classifiers are built on a knowledge base modelled as a fuzzy rule "if-then".  ...  The proposed classifiers FSLS, FTS and FDE are tested on the benchmark KDD'99 intrusion dataset and compared with some well-known existing techniques for intrusion detection.  ...  In this paper, we consider the intrusion detection as a pattern classification where a connection's attributes constitutes a pattern that should be assigned to one of existing classes.  ... 
doi:10.4018/ijamc.2014040103 fatcat:ay2cgqdn65ckzivbiueot3yfky

A Multi-Source Data Oriented Network Intrusion Detection Framework Based on Rough Set

Huilin Wu, Wenjuan Wu, Shiying =Yu
2019 DEStech Transactions on Computer Science and Engineering  
In this paper, we propose a new multi-source data oriented framework based on Rough Set for network intrusion detection.  ...  As a result, there is a need for a framework that can detect network attacks accurately and effectively, while can process multisource data at the same time.  ...  INTRUSION DETECTION ALGORITHM BASED ON RST Intrusion detection algorithm can be divided into 2 stages, detection rules generation and detection model learning and updating.  ... 
doi:10.12783/dtcse/iciti2018/29119 fatcat:52dhsbdj3fc3nhxhosaj5vjh3e

An Agent Based Intrusion Detection Model for Mobile Ad Hoc Networks

B. M. Reshmi, S. S. Manvi, Bhagyavati
2006 Mobile Information Systems  
The model comprises of a set of static and mobile agents, which are used to detect intrusions, respond to intrusions, and distribute selected and aggregated intrusion information to all other nodes in  ...  As such, there is a need to complement traditional security mechanisms with efficient intrusion detection and response systems.  ...  Acknowledgement We thank the anonymous reviewers for giving us good suggestions to improve the quality of the paper.  ... 
doi:10.1155/2006/921047 fatcat:ioiloff35jdofkxpsni5o3psiy

Web Intrusion Detection System through Crawler's Event Analysis

Ponmaniraj S
2020 International Journal of Advanced Trends in Computer Science and Engineering  
Intrusions are obtaining on the following categories, Stand alone system, Networks and Web oriented intrusions.  ...  There are more possibilities on web oriented intrusions due to web sites and their referral links are coming from number of intermediate agents.  ...  The reliability of a web links are processed on the basis of data patterns from block list and white list [15] . KDD99 dataset is specialized for intrusion detection mechanisms.  ... 
doi:10.30534/ijatcse/2020/03932020 fatcat:gtlx7uikqbes5pmjvdj2ujrbzm

An overview of Intrusion Detection within an Information System: The Improvment by Process Mining

Nkondock Mi Bahanag Nicolas, Atsa Etoundi Roger
2022 Network and Communication Technologies  
The purpose of this paper is to present an overview of existing intrusion detection techniques compared to a new issue based on process mining used for event logs analysis to detect abnormal events that  ...  Research in intrusion detection field is still looking for solutions of such relevant problems.  ...  The reason is simple: ( Proctor, 2000) The interest of Network based Intrusion Detection is on the analyze of packets within the net-work while Host based Intrusion is orientated on logs, the starting  ... 
doi:10.5539/nct.v7n1p55 fatcat:27hzjlrxcbfz5fdiutpn2luyae

CONDOR: A Hybrid IDS to Offer Improved Intrusion Detection

David J. Day, Denys A. Flores, Harjinder Singh Lallie
2012 2012 IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications  
new hybrid IDS named CONDOR (COmbined Network intrusion Detection ORientate), which is designed to offer superior pattern analysis and anomaly detection by reducing false positive rates and administrator  ...  Intrusion Detection Systems are an accepted and very useful option to monitor, and detect malicious activities.  ...  One integrated database is created which is replicated on each of the hosts for local anomaly analysis. ADCOIN combines host and network intrusion detection into one model.  ... 
doi:10.1109/trustcom.2012.110 dblp:conf/trustcom/DayFL12 fatcat:c4l7ixyfhbdozgdxao2muc4gzm

Unsupervised Intrusion Detection System for Unmanned Aerial Vehicle with Less Labeling Effort [article]

Kyung Ho Park, Eunji Park, Huy Kang Kim
2020 arXiv   pre-print
Along with the importance of safety, an IDS has become a significant task in the real world. Prior studies proposed various intrusion detection models for the UAV.  ...  Past rule-based approaches provided a concrete baseline IDS model, and the machine learning-based method achieved a precise intrusion detection performance on the UAV with supervised learning models.  ...  To overcome the drawback, several studies applied machine learning models to detect intrusions on the UAV. Tan et al.  ... 
arXiv:2011.00540v1 fatcat:3rqyfbowtbd6jdprpa62lu2f5i

Comparison of Data Mining Techniques for Building Network Intrusion Detection Models

Harsha Kosta, Darshan Bhavesh
2016 International Journal of Computer Applications  
Intrusion detection is a detection of encroachment on the personal network or the private network to breach the security systems.  ...  These techniques are implemented on the dataset for the experiment, since decision tree C5.0 technique and support vector machine (SVM) in general widely used in intrusion experiment data i.e.  ...  These software packages for intrusion detection are mostly signature-oriented with almost or no state information on record.  ... 
doi:10.5120/ijca2016909840 fatcat:skxh3gbxkvdp7dstnkqdbgovva

Hybrid Intelligent Intrusion Detection System

Norbik Bashah, Idris Bharanidharan Shanmugam, Abdul Manan Ahmed
2007 Zenodo  
Artificial Intelligence plays a driving role in security services. This paper proposes a dynamic model Intelligent Intrusion Detection System, based on specific AI approach for intrusion detection.  ...  For host based intrusion detection we use neural-networks along with self organizing maps.  ...  Timebased Inductive Machine (TIM) for intrusion detection [3] learns sequential patterns.  ... 
doi:10.5281/zenodo.1061257 fatcat:rryehjccwfbsvckml57bsvdtay

Anomaly-based network intrusion detection: Techniques, systems and challenges

P. García-Teodoro, J. Díaz-Verdejo, G. Maciá-Fernández, E. Vázquez
2009 Computers & security  
Finally, we outline the main challenges to be dealt with for the wide scale deployment of anomaly-based intrusion detectors, with special emphasis on assessment issues. (J.  ...  Threat Intrusion detection Anomaly detection IDS systems and platforms Assessment a b s t r a c t The Internet and computer networks are exposed to an increasing number of security threats.  ...  , stochastic modelling, pattern matching Intelligent Intrusion Detection (IIDS) Mississippi State University Fuzzy data mining Minnesota INtrusion Detection System (MINDS) University of Minnesota  ... 
doi:10.1016/j.cose.2008.08.003 fatcat:sm4ygjfx4rdvxmjmoqhmkc2ecm

Table of Contents

2021 2021 5th International Conference on Pattern Recognition and Image Analysis (IPRIA)  
Micro-Expression Recognition Using Histogram of Image Gradient Orientation on Diagonal Planes 21. Persian Language Model based on BiLSTM Model on COVID-19 Corpus 22.  ...  Violence detection using pretrained models 14. A Density-based Undersampling Approach to Intrusion Detection 15. Video Event Recognition using Two-Stream Convolutional Neural Networks 16.  ... 
doi:10.1109/ipria53572.2021.9483452 fatcat:drscmcfa5vhnjadd7k2vcb3nma

A Survey on Intrusion Detection Systems for Fog and Cloud Computing

Victor Chang, Lewis Golightly, Paolo Modesti, Qianwen Ariel Xu, Le Minh Thao Doan, Karl Hall, Sreeja Boddu, Anna Kobusińska
2022 Future Internet  
The paper focuses on a Software-as-a-Service (SaaS) and intrusion detection, which provides an effective and resilient system structure for users and organizations.  ...  state-of-the-art review of intrusion detection systems and their principles.  ...  In a study, the researchers examined the current process for intrusion detection and prevention in service-oriented vehicular networks [12] .  ... 
doi:10.3390/fi14030089 fatcat:wxlz2xeduzdpvbyf63rwosal7e

Application of data mining technology in detecting network intrusion and security maintenance

Yongkuan Zhu, Gurjot Singh Gaba, Fahad M. Almansour, Roobaea Alroobaea, Mehedi Masud
2021 Journal of Intelligent Systems  
The improved and tested detection model is then applied to a new intrusion detection system.  ...  A significant improvement of 90.57% can be seen in detecting new attack type intrusion detection using the proposed algorithm.  ...  The future work in this field will address the shortcomings in the research of IDS based on data mining technology, such as the high cost of the improved Apriori algorithm in space.  ... 
doi:10.1515/jisys-2020-0146 fatcat:fu2lpgcxrrcgbi3geye5srh5he

A Review on Network Intrusion Detection System Using Open Source Snort

Sakshi Sharma, Manish Dixit
2016 International Journal of Database Theory and Application  
IDS works on the concept of investigating all the incoming packets for the detection of any malicious activity. This is a survey paper on the various enhancements over the decades on IDS.  ...  Its used world widely in Intrusion Detection and Prevention.  ...  Misuse Based Intrusion Detection: It detects malicious code based on the specific known patterns (which is known as a signature).  ... 
doi:10.14257/ijdta.2016.9.4.05 fatcat:szzgkywylvhsxhfyidoq3ynawm
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