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A Comparative Study of AI-based Intrusion Detection Techniques in Critical Infrastructures [article]

Safa Otoum and Burak Kantarci and Hussein Mouftah
2020 arXiv   pre-print
In this paper, we present a comparative study of Artificial Intelligence (AI)-driven intrusion detection systems for wirelessly connected sensors that track crucial applications.  ...  Results present the performance metrics for three different IDSs namely the Adaptively Supervised and Clustered Hybrid IDS (ASCH-IDS), Restricted Boltzmann Machine-based Clustered IDS (RBC-IDS) and Q-learning  ...  In this study, we present a comparative study between machine leads to huge vulnerabilities.  ... 
arXiv:2008.00088v1 fatcat:itetvn2n3ratrn4shhvn2tnjiq

DDOS Botnets Attacks Detection in Anomaly Traffic: A Comparative Study

Ahmed A. Elsherif, Arwa A. Aldaej
2020 Journal of Information Security and Cybercrimes Research  
One of the major challenges that faces the acceptance and growth rate of business and governmental sites is a Botnet-based DDoS attack.  ...  Nonetheless, it is not that easy to detect and tackle flooding DDoS attacks, owing to the significant number of attacking machines, the usage of source-address spoofing, and the common areas shared between  ...  In this paper, a comparative study of the machine learning techniques is studied to find the best algorithm that should be utilized in order to detect anomalous attacks in network traffic.  ... 
doi:10.26735/zrxn1433 fatcat:uxa2ulvcyvhzje5wjjic7fjjhy

A Comparative Study of Anomaly Detection Techniques for Smart City Wireless Sensor Networks

Victor Garcia-Font, Carles Garrigues, Helena Rifà-Pous
2016 Sensors  
As a result of this study, we conclude that one-class Support Vector Machines is the most appropriate technique.  ...  Then, we compare frequently used anomaly detection techniques to disclose these attacks. We evaluate the algorithms under different requirements on the available network status information.  ...  For instance, the authors of [16] compare several unsupervised approaches based on local outlier factor, near neighbors, Mahalanobis distance and Support Vector Machines to detect intrusions in conventional  ... 
doi:10.3390/s16060868 pmid:27304957 pmcid:PMC4934294 fatcat:l4q3ci5mwbfztfckuovc5gxmmy

A Comparative Study of Traffic Generators: Applicability for Malware Detection Testbeds

Matthew Swann, Joseph Rose, Gueltoum Bendiab, Stavros Shiaeles, Nick Savage
2020 Journal of Internet Technology and Secured Transaction  
Mainly, the comparative experiments examine the strengths and limitations of these tools, for malicious traffic-which can help the research community to choose the most suitable one to assess the performance  ...  The accuracy of the simulation results depends strongly on the performance and reliability of the used generator.  ...  They also investigated the impact of different I/O frameworks on the performance of the studied NTGs. Another work by A. Botta et al.  ... 
doi:10.20533/jitst.2046.3723.2020.0085 fatcat:vajlvaqzjfhuhkxmxnlotpgr64

Feature Fusion for Fingerprint Liveness Detection: a Comparative Study

Amirhosein Toosi, Andrea Bottino, Sandro Cumani, Pablo Negri, Pietro Luca Sottile
2017 IEEE Access  
Spoofing attacks carried out using artificial replicas are a severe threat for fingerprint based biometric systems and, thus, require the development of effective countermeasures.  ...  methods, such as the ones based on Convolutional Neural Networks.  ...  Computational resources were provided by HPC@POLITO, a project of Academic Computing within the Department of Control and Computer Engineering at the Politecnico di Torino (  ... 
doi:10.1109/access.2017.2763419 fatcat:tgbj2xyiejb6bcvky7l4uhj4se

Web Description Logic Rule Generation And Other Machine Learning Algorithms – A Comparative Study

Revathi S
2020 International Journal of Advanced Trends in Computer Science and Engineering  
Based on the sharing threshold, the algorithm can detect vulnerable users and safeguard them from any potential threats.  ...  The research presents a comparison study of WDLRG in contrast to rest of the ML Techniques namely Decision tree and Bayesian network.  ...  The bar chart presents, the comparison of graph performance for detecting vulnerable user profile processing employed in the classification methods to compare various machine learning systems such as the  ... 
doi:10.30534/ijatcse/2020/140922020 fatcat:ajjat7h5obcr7ohfyrfd7dphpu


Salihu Alhasan, Ajayi Ebenezer Akinyemi, Daniel Dauda Wisdom
2020 International Journal of Engineering Applied Sciences and Technology  
In this paper, we have compared four algorithms of Machine Learning models which are namely: Naives Bayes (NB), Decision trees (J48), Support Vector machines (SVN), and Sequential Machine optimization  ...  ABSTRACTS -Data mining provide decision support for intrusion management, and also help in Intrusion Detection System (IDS) in detecting of new vulnerabilities and intrusions by discovering unknown patterns  ...  Machine Learning: is the prediction, based on known properties learned from the training data or is a scientific discipline concerned with the design and allow computers to evolve behaviors based on empirical  ... 
doi:10.33564/ijeast.2020.v05i06.014 fatcat:rkurjt3n6fclpbkpj3qhxv6you

Crowdsourcing Under Data Poisoning Attacks: A Comparative Study [chapter]

Farnaz Tahmasebian, Li Xiong, Mani Sotoodeh, Vaidy Sunderam
2020 Lecture Notes in Computer Science  
We use several evaluation metrics to analyze the robustness or susceptibility of truth inference methods against various attacks, which sheds light on the resilience of existing methods and ultimately  ...  A key component of these crowdsourcing applications is truth inference which aims to derive the true answer for a given task from the user-contributed data, e.g. the existence of objects in an image, or  ...  Data poisoning attacks for machine learning (ML) algorithms have been increasingly studied recently [2, 5, 18, 23, 37, 40, 47] .  ... 
doi:10.1007/978-3-030-49669-2_18 fatcat:xnytdkglavfh5f2ixm7euz2wwy

A comparative study on machine learning based algorithms for prediction of motorcycle crash severity

Lukuman Wahab, Haobin Jiang, Yanyong Guo
2019 PLoS ONE  
The three machine learning based algorithms were compared with one another and the statistical model: multinomial logit model (MNLM).  ...  The results of the study reveal that the predictions of machine learning algorithms are superior to the MNLM in accuracy and effectiveness, and the RF-based algorithms show the overall best agreement with  ...  for providing the data for the study.  ... 
doi:10.1371/journal.pone.0214966 pmid:30947250 pmcid:PMC6448880 fatcat:hnwitmtzgvgtrnfon7vkqrox7y

Cybersecurity Enterprises Policies: A Comparative Study

Alok Mishra, Yehia Ibrahim Alzoubi, Asif Qumer Gill, Memoona Javeria Anwar
2022 Sensors  
One part of the cyberdefense mechanism is building an enterprises' security policies library, for consistent implementation of security controls.  ...  Furthermore, the findings of this study reveal that the importance of cybersecurity requirements differ across multiple organizations.  ...  Acknowledgments: We are thankful to Maha Samir of Atilim University, for assisting in this study. Conflicts of Interest: The authors declare no conflict of interest. Appendix A  ... 
doi:10.3390/s22020538 pmid:35062504 pmcid:PMC8778887 fatcat:kevdlnizqfajvf7xvglho6snui

A comparative experimental study of software rejuvenation overhead

J. Alonso, R. Matias, E. Vicente, A. Maria, K.S. Trivedi
2013 Performance evaluation (Print)  
In this paper we present a comparative experimental study of the main software rejuvenation techniques developed so far to mitigate the software aging effects.  ...  Finally, based on these research findings we present comprehensive guidelines to support decision making during the design of rejuvenation scheduling algorithms, as well as in selecting the appropriate  ...  We also thank CNPq (National Research Council of Brazil) for the financial support. We also thank Daniel Tes for his help during the test bed setup.  ... 
doi:10.1016/j.peva.2012.09.002 fatcat:fkbihmdmb5d7vjsr3sdcdy35ym

Testing Deep Learning Models: A First Comparative Study of Multiple Testing Techniques [article]

Mohit Kumar Ahuja, Arnaud Gotlieb, Helge Spieker
2022 arXiv   pre-print
We also provide a first experimental comparative study on a classical benchmark used in VBS and discuss its results.  ...  Deep Learning (DL) has revolutionized the capabilities of vision-based systems (VBS) in critical applications such as autonomous driving, robotic surgery, critical infrastructure surveillance, air and  ...  We provide an initial experimental comparative analysis of different testing technique on a VBSrelevant case study.  ... 
arXiv:2202.12139v1 fatcat:lblcnzhhwbfcpa6lug6c3vrt6q

A Comparative Study of Web Content Management Systems

Jose-Manuel Martinez-Caro, Antonio-Jose Aledo-Hernandez, Antonio Guillen-Perez, Ramon Sanchez-Iborra, Maria-Dolores Cano
2018 Information  
On the other hand, the visible part of a website, i.e., what a visitor sees, is called the front-end.  ...  On the other hand, the visible part of a website, i.e., what a visitor sees, is called the front-end.  ...  Antonio Guillen-Perez and Ramon Sanchez-Iborra contributed with the selection of tools, initial testing, and the state of the art. Antonio-Jose Aledo-Hernandez performed the experiments.  ... 
doi:10.3390/info9020027 fatcat:oofzxaqkbrd5fmahmblh24drqm

A Comparative Evaluation Study of Automated Gait Recognition based on Spatiotemporal Feature and Different Neural Network Classifiers

Noha A.Hikal
2013 International Journal of Computer Applications  
The performance of four artificial neural networks (ANNs) based classifiers was evaluated and tested, based on spatiotemporal features.  ...  The results show that discrete wavelet transforms and support vector machine recognition technique provides a recognition rates up to 94%.  ...  Finally, the machine learning phase based on supervised ANN's is employed to accomplish the learning process from these features and get the final recognition result.  ... 
doi:10.5120/11610-6991 fatcat:lswwmonifnhchjsfuax44iavda

Data Mining Techniques for Software Effort Estimation: A Comparative Study

Karel Dejaeger, Wouter Verbeke, David Martens, Bart Baesens
2012 IEEE Transactions on Software Engineering  
This study addresses this issue by reporting on the results of a large scale benchmarking study.  ...  (MARS, multilayered perceptron neural networks, radial basis function networks, and least squares support vector machines), and estimation techniques that do not explicitly induce a model (e.g., a case-based  ...  They extend their gratitude to the Flemish Research Fund for financial support to the authors (Odysseus grant G.0915.09 to Bart Baesens and postdoctoral research grant to David Martens).  ... 
doi:10.1109/tse.2011.55 fatcat:ykehdbylzbbyznglrzpgb5wa7y
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