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Proposed vision for Network Intrusion Detection System using Latent Semantic Analysis and data mining

Ikhlas K. Gbashi, Soukaena H. Hashem, Saad K. Majeed
2014 2014 6th Computer Science and Electronic Engineering Conference (CEEC)  
In traditional and current Network Intrusion Detection Systems (NIDSs) the most important stage of them is; how to reduce the features space dimension to extract the only critical features to detect the  ...  Principle Component Analysis (PCA) is needed to detect intrusion by transform a set of features space to a lower dimension space retaining the variability of the original data from any change.  ...  INTRODUCTION Intrusion detection is a process of gathering intrusion related knowledge occurring in the process of monitoring the events and analyzing them for sign or intrusion.  ... 
doi:10.1109/ceec.2014.6958547 fatcat:i5q5bgpryfc27njb4zbcxifioq

A Systematic Review of Defensive and Offensive Cybersecurity with Machine Learning

Imatitikua D. Aiyanyo, Hamman Samuel, Heuiseok Lim
2020 Applied Sciences  
Our findings identify the frequently used machine learning methods within supervised, unsupervised, and semi-supervised machine learning, the most useful data sets for evaluating intrusion detection methods  ...  Ultimately, this paper seeks to provide a base for researchers that wish to delve into the field of machine learning for cybersecurity.  ...  Uses of Evolutionary Computation Algorithms and Swarm Intelligence for Network Intrusion Detection 5 A33 [15] 2015 An Improved Bat Algorithm Driven by Support Vector Machines for Intrusion Detection  ... 
doi:10.3390/app10175811 fatcat:xnuwg7qumbbzzmuxlsh7d33cam

Machine Learning for Anomaly Detection: A Systematic Review

Ali Bou Nassif, Manar Abu Talib, Qassim Nasir, Fatima Mohamad Dakalbab
2021 IEEE Access  
analysis of SVM and its stacking with other classification algorithm for intrusion detection" Conf. 2016 [43] A16 "FRaC: a feature-modeling approach for semi-supervised and unsupervised anomaly detection  ...  2018 [171] A146 "Network Anomaly Traffic Detection Method Based on Support Vector Machine" Conf. 2016 [172] A147 "Anomaly detection of spacecraft based on least squares support vector machine" Conf  ... 
doi:10.1109/access.2021.3083060 fatcat:vv7qthbvqjdz7ksm3yosulk22q

A Survey of Intrusion Detection Systems Leveraging Host Data [article]

Tarrah R. Glass-Vanderlan and Michael D. Iannacone and Maria S. Vincent and Qian Chen and Robert A. Bridges
2018 arXiv   pre-print
This survey focuses on intrusion detection systems (IDS) that leverage host-based data sources for detecting attacks on enterprise network.  ...  Finally, challenges, trends, and broader observations are throughout the survey and in the conclusion along with future directions of IDS research.  ...  The research is based upon work supported by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via the Department of Energy (DOE) under  ... 
arXiv:1805.06070v2 fatcat:jrihtcjmhjgdbl4kkqmbgyiqs4

Intrusion Detection Model Based on TF.IDF and C4.5 Algorithms

Khaldoon AWADH, Ayhan AKBAŞ
2020 Journal of Polytechnic  
the performance of Intrusion Detection Systems (IDS).  ...  Intrusion Detection Model Based on TF.IDF and C4.5 Algorithms ABSTRACT In recent years, the use of machine learning and data mining technologies has drawn researchers' attention to new ways to improve  ...  Deshmukh, Ghorpade, and Padiya [15] depicted a comparative performance of different classification algorithms of Naive Bayes, AD Tree, and NB Tree by using benchmark NSL-KDD 99 dataset.  ... 
doi:10.2339/politeknik.693221 fatcat:epxaok5jdjcrtjkwgk4jrjuyva

Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges [article]

Muhammad Usama, Junaid Qadir, Aunn Raza, Hunain Arif, Kok-Lim Alvin Yau, Yehia Elkhatib, Amir Hussain, Ala Al-Fuqaha
2017 arXiv   pre-print
detection, Internet traffic classification, and quality of service optimization.  ...  Unsupervised learning is interesting since it can unconstrain us from the need of labeled data and manual handcrafted feature engineering thereby facilitating flexible, general, and automated methods of  ...  better than the Naïve Bayes classifier in terms of accuracy on the NSL-KDD intrusion detection dataset.  ... 
arXiv:1709.06599v1 fatcat:llcg6gxgpjahha6bkhsitglrsm

IoT Vulnerability Assessment for Sustainable Computing: Threats, Current Solutions, and Open Challenges

Pooja Anand, Yashwant Singh, Arvind Selwal, Mamoun Alazab, Sudeep Tanwar, Neeraj Kumar
2020 IEEE Access  
[153] Intrusion Detection NSL-KDD dataset DR=84.86 FAR =4.86 To explore other Machine learning tech- niques to counter the attack. To detect intrusions on other layers.  ...  [157] Distributed attack detection scheme NSL-KDD dataset AR = 98.27% DR=96.5% FAR = 2.57% Analysis of payload data.  ... 
doi:10.1109/access.2020.3022842 fatcat:ifkplk2lsjhupkt4c42fovqpta

Federated Learning: A Distributed Shared Machine Learning Method

Kai Hu, Yaogen Li, Min Xia, Jiasheng Wu, Meixia Lu, Shuai Zhang, Liguo Weng, Siew Ann Cheong
2021 Complexity  
On the basis of classical FL algorithms, several federated machine learning algorithms are briefly introduced, with emphasis on deep learning and classification and comparisons of those algorithms are  ...  First of all, this paper introduces the development process, definition, architecture, and classification of FL and explains the concept of FL by comparing it with traditional distributed learning.  ...  Acknowledgments is research was supported by the National Natural Science Foundation of China (42075130, 61773219, and 61701244) and the Key Special Project of the National Key R&D Program (2018YFC1405703  ... 
doi:10.1155/2021/8261663 fatcat:ahr2rpg2indqzg4h3zzda3co5a

Conference Program

2021 2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)  
Khalafalla has worked in various fields of the industry, including Commercial construction and Oil & Gas. Dr. Khalafalla has an MBA degree, and he is Professional Project Management (PMP) certified.  ...  He received his Ph.D. degree in Civil Engineering with an emphasis on Construction Management from Auburn University and an M.S. degree in Civil Engineering from The University of Tennessee at Chattanooga  ...  area of Environment and Sustainable Development at the University of Bahrain.  ... 
doi:10.1109/3ict53449.2021.9581455 fatcat:zgaclsoapjbhbmjmki7bjltre4

Special Issue: 100 Years of Alan Turing and 20 Years of SLAIS

Dunja Mladeni´c, Stephen Muggleton, Ivan Bratko, Anton Železnikar, Matjaž Gams, Jožef Stefan, Drago Torkar, Jožef Stefan, Juan Carlos, Augusto, Argentina, Costin Badica (+12 others)
2013 unpublished
We observe that In this paper we present a clustering based classification method and apply it in network anomaly detection.  ...  Here we present its main methodological concepts, contributions to the theory and practice of decision support, and outline a history of its development and evolution.  ...  Acknowledgement This work is an outcome of a research project funded by MCIT, New Delhi.  ... 

Special Issue: Advances in Network Systems

Andrzej Chojnacki, Andrzej Kowalski, Bohdan Macukow, Maciej Grzenda, Anton Železnikar, Matjaž Gams, Jožef Stefan, Drago Torkar, Jožef Stefan, Juan Carlos, Augusto, Argentina (+13 others)
2012 unpublished
The main idea of providing a forum for academia and application-oriented research was fulfilled by the organizers of the event.  ...  To stimulate the cooperation between commercial research community and academia, the first edition of Frontiers in Network Applications and Network Systems symposium was organized in 2012.  ...  Acknowledgement This work is supported by the Ministry of Education, Youth, and Sport of the Czech Republic -University spec. research -1311.  ...