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Detecting Malicious DNS over HTTPS Traffic in Domain Name System using Machine Learning Classifiers

Yaser M. Banadaki
2020 Journal of Computer Sciences and Applications  
The results show that LGBM and XGBoost algorithms outperform the other algorithms in almost all the classification metrics reaching the maximum accuracy of 100% in the classification tasks of layers 1  ...  LGBM algorithms only misclassified one DoH traffic test as non-DoH out of 4000 test datasets.  ...  The weakest performance results in 99.4% in calculating the cross-validation classification metrics of extra tree algorithms in classifying DoH traffic from non-DoH traffic in layer 1.  ... 
doi:10.12691/jcsa-8-2-2 fatcat:nqcp2mswbrc3ndte3oh4vrtuia

A robust algorithm for detection and classification of traffic signs in video data

Thanh Bui-Minh, Ovidiu Ghita, Paul F. Whelan, Trang Hoang
2012 2012 International Conference on Control, Automation and Information Sciences (ICCAIS)  
The TSR algorithm has been validated using video sequences that include the most important categories of signs that are used to regulate the traffic on the Irish and UK roads, and it achieved 87.6% sign  ...  The main novel elements of our TSR algorithm are given by the approach that has been developed for traffic sign classification and by the experimental evaluation that was employed to identify the optimal  ...  In our future studies we will focus on the implementation of robust traffic sign tracking algorithms that will be used to enhance the confidence of the traffic sign recognition in video data and on the  ... 
doi:10.1109/iccais.2012.6466568 fatcat:xb5qtcrqvrab5e7dyctziaqs34

A New Network Traffic Classification Method Based on Classifier Integration

Zhang Luoshi, Xue Yibo, Bao Yuanyuan
2015 International Journal of Grid and Distributed Computing  
The experimental results validated the effectiveness of this method in the classification of actual network traffic of little class.  ...  Based on active learning and SVM algorithms, Wang Yipeng et al. [10] achieved the classification of unknown network protocol traffic only depending on the payload information in untreated network traffic  ...  To validate CMM method's independence of the sub-classifier's classification algorithm, Naïve Bayes algorithm and Bayes Net algorithm were additionally selected as the classification algorithms of the  ... 
doi:10.14257/ijgdc.2015.8.3.29 fatcat:xbe7i36z65htvlmevqt5adnpgm

Comparative Analysis of Background Subtraction and CNN Algorithms for Mid-Block Traffic Data Collection and Classification

Ubaid Illahi, Mohammad Shafi Mir
2020 International journal of mathematical, engineering and management sciences  
Classification of vehicles in the traffic stream is a pre-requisite for planning and designing the facilities for road-users.  ...  To check the reliability of these algorithms, the outputs produced were validated against the data obtained from Kachkoot Toll Plaza, India.  ...  Acknowledgment The authors would like to thank the Project Director PIU Srinagar, National Highway Authority of India, Ministry of Road Transport and Highways, Government of India for providing the video-recordings  ... 
doi:10.33889/ijmems.2020.5.6.107 fatcat:6xoeja6kubbo3izqz3xkas3eny

Automated Classification of Network Traffic Anomalies [chapter]

Guilherme Fernandes, Philippe Owezarski
2009 Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering  
We validate our algorithm on two different datasets: the METROSEC project database and the MAWI traffic repository.  ...  This paper presents a new algorithm for automated classification of network traffic anomalies.  ...  Acknowledgment This work has been done in the framework of the ECODE project funded by the European commission under grant FP7-ICT-2007-2/223936.  ... 
doi:10.1007/978-3-642-05284-2_6 fatcat:c5echqmsibasdnh377sfewrshm

Abnormal Network Traffic Detection Based on Semi-Supervised Machine Learning

2018 DEStech Transactions on Engineering and Technology Research  
Machine learning can be used to abstract the characters of a class of objects.  ...  Network intrusions will cause abnormal network traffic flow. The abnormal network traffic detection can be used to identify the network intrusions.  ...  Classification Model First, we validate the feasibility of the decision tree and the KNN algorithm by cross validation on the NSL-KDD dataset.  ... 
doi:10.12783/dtetr/ecame2017/18466 fatcat:ei52nx7lbnbo5i42ebfoql3waq

Real Time Traffic Light Detection by Autonomous Vehicles using Artificial Neural Network Techniques

The work carried out in this research makes use of two Artificial Intelligence technique, these techniques are compared in accomplishing the task of traffic light detection in real time.  ...  These automobiles are capable of sensing their environment and moving with little or no human input. The main goal of this research is to detect traffic light in real-time for autonomous vehicles.  ...  Vignesh, Radhika B Raman and Ullas V B for providing the literature survey and implementing a part of this work as their project.  ... 
doi:10.35940/ijitee.j9355.0881019 fatcat:66tzfehs6vcx3ia3kw4qipw2my

Machine Learning Classification of Port Scanning and DDoS Attacks: A Comparative Analysis

Muhammad Aamir, Syed Sajjad Hussain Rizvi, Manzoor Ahmed Hashmani, Muhammad Zubair, Jawwad Ahmed
2021 Mehran University Research Journal of Engineering and Technology  
In this paper, the benefits of machine learning are taken into consideration for classification of port scanning and DDoS attacks in a mix of normal and attack traffic.  ...  Cyber security is one of the major concerns of today's connected world.  ...  ACKNOWLEDGMENT The authors are thankful to anonymous reviewers for suggesting improvements in the quality of this paper.  ... 
doi:10.22581/muet1982.2101.19 doaj:4ab4312997f74269a802fc54134fc5bd fatcat:lympwyui5bdoji5ttf6b2jrj4a

VPN Encrypted Traffic classification using XGBoost

2021 International Journal of Emerging Trends in Engineering Research  
To illustrate the merit of the proposed model, a comparison was made with sixteen different classification algorithms  ...  Virtual Private Networks (VPNs) have become one famous communication forms on the Internet. In this study, a new model for traffic classification into VPN or non-VPN is proposed.  ...  The result of the proposed model was validated using 10-fold cross-validation.  ... 
doi:10.30534/ijeter/2021/20972021 fatcat:gjwy64o2qncathedum5elmldpm

Mathematical validation of proposed machine learning classifier for heterogeneous traffic and anomaly detection

Azidine Guezzaz, Younes Asimi, Mourade Azrour, Ahmed Asimi
2021 Big Data Mining and Analytics  
A reliable training algorithm is proposed to optimize the weights, and a recognition algorithm is used to validate the model.  ...  The recognition of new elements is possible based on predefined classes. Intrusion detection systems suffer from numerous vulnerabilities during analysis and classification of data activities.  ...  The validation of the new classifier model based on the proposed machine learning algorithm is achieved on the basis of suggested solutions that guarantee an efficient and fast analysis.  ... 
doi:10.26599/bdma.2020.9020019 fatcat:naukv2mmkbfv7k3ahdimqb3mcu

Two methods for reliable classification of network traffic

Mikhail Dashevskiy, Zhiyuan Luo
2012 Progress in Artificial Intelligence  
In this paper, we consider the problem of reliable network traffic classification.  ...  Experiments on publicly available real network traffic datasets in the on-line setting show these two methods can perform well and produce reliable classifications.  ...  Traffic classification can be defined as methods of classifying traffic data based on features passively observed in the traffic, according to specific classification goals.  ... 
doi:10.1007/s13748-012-0019-5 fatcat:7m5u7rp54vcorg7dflcogl6f7m

Classification of Traffic Accident Information Using Machine Learning from Social Media

Dody Agung Saputro
2020 International Journal of Emerging Trends in Engineering Research  
of models using K-fold validation method.  ...  To find out whether the tweet is true about accident information, then we do a word embedding using FastText method and classification with SVM, KNN, and Naïve Bayes algorithms then testing the accuracy  ...  ] and optimization of web classification using Firefly algorithm based on Naïve Bayes [15] .  ... 
doi:10.30534/ijeter/2020/04832020 fatcat:taam6lhoqvg2xfns7w64fbblcm

An Approach Based on the Improved SVM Algorithm for Identifying Malware in Network Traffic

Bo Liu, Jinfu Chen, Songling Qin, Zufa Zhang, Yisong Liu, Lingling Zhao, Jingyi Chen
2021 Security and Communication Networks  
On average, the NTMI approach achieves an accuracy of 92.5% and a false positive rate of 5.527%.  ...  The OFSVM algorithm solves the problem that the original SVM algorithm is not satisfactory for classification from two aspects, i.e., parameter optimization and kernel function selection.  ...  And then, we present the OFSVM algorithm based on the SVM algorithm for classifying network traffic and improving the accuracy of classification in network traffic. e OFSVM algorithm improves the SVM algorithm  ... 
doi:10.1155/2021/5518909 doaj:ac9b79b221734b5fa4fd12c32996eae4 fatcat:ydgawkifk5db5d3aba4yfmb4ra

Video Quality Representation Classification of Encrypted HTTP Adaptive Video Streaming

2018 KSII Transactions on Internet and Information Systems  
This highlights the need for new traffic classification methods for encrypted HTTP adaptive video streaming to enable smart traffic shaping.  ...  The increasing popularity of HTTP adaptive video streaming services has dramatically increased bandwidth requirements on operator networks, which attempt to shape their traffic through Deep Packet inspection  ...  In the following experiments we used k = 14. bins in the codebook learning algorithm Fig. 3 . 3 Codebook learning algorithm cross validation identification rate on the training dataset for a different  ... 
doi:10.3837/tiis.2018.08.014 fatcat:miqee236ifh7vonh2fj6gozb7y

Analysis of Various Network Traffic Classification Techniques

Shivam Puri, Sukhpreet Kaur
2021 CGC International Journal of Contemporary Technology and Research  
The various network traffic classification techniques are reviewed in terms of certain parameters.  ...  On the basis of observed attributed of an object within the system, another attributed is predicted using new model.  ...  Using the inclusion criterion, which mainly depends on the techniques, the relevant work of network traffic classification algorithms is retrieved from the enormous collection of data given by search engines  ... 
doi:10.46860/cgcijctr.2021.12.31.261 fatcat:ipw5jidymzfh7f77tfumfizroq
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