scholarly journals Analysis of Malware Dns Attack on the Network Using Domain Name System Indicators

2020 ◽  
Vol 2 (1) ◽  
pp. 131-153
Author(s):  
Beni Brahara ◽  
Dedy Syamsuar ◽  
Yesi Novaria Kunang
Keyword(s):  
Decision Tree ◽  
Network Traffic ◽  
Life Time ◽  
Network Analyzer ◽  
Domain Name System ◽  
Domain Name ◽  
Domain Names ◽  
Decision Tree Method ◽  
Short Times ◽  
Tree Method

University of Bina Darma Palembang has its own DNS server and in this study using log data from the Bina Darma University DNS server as data in the study, DNS log server data is analyzed by network traffic, using Network Analyzer tools to see the activity of a normal traffic or anomaly traffic, or even contains DGA Malware (Generating Algorthm Domain).DGA malware produces a number of random domain names that are used to infiltrate DNS servers. To detect DGA using DNS traffic, NXDomain. The result is that each domain name in a group domain is generated by one domain that is often used at short times and simultaneously has a similar life time and query style. Next look for this pattern in NXDomain DNS traffic to filter domains generated algorithmically that the domain contains DGA. In analyzing DNS traffic whether it contains Malware and whether network traffic is normal or anomaly, in this study it detects Malwere DNS From the results of the stages of the suspected domain indicated by malware, a suspected domain list table is also created and also a suspected list of IP addresses. To support the suspected domain analysis results, info graphic is displayed using rappidminer tools to test decisions that have been made using the previous tools using the Decision Tree method.

scholarly journals NETWORK TRAFFIC ANOMALIES IDENTIFICATION BASED ON CLASSIFICATION METHODS / TINKLO SRAUTO ANOMALIJŲ IDENTIFIKAVIMAS, TAIKANT KLASIFIKAVIMO METODUS

2015 ◽  
Vol 7 (3) ◽  
pp. 340-344
Author(s):  
Donatas Račys ◽  
Dalius Mažeika
Keyword(s):  
Decision Tree ◽  
Computer Networks ◽  
Network Traffic ◽  
Detection Methods ◽  
Classification Methods ◽  
Advantages And Disadvantages ◽  
Decision Tree Method ◽  
And Performance ◽  
Tree Method ◽  
Learning Data

A problem of network traffic anomalies detection in the computer networks is analyzed. Overview of anomalies detection methods is given then advantages and disadvantages of the different methods are analyzed. Model for the traffic anomalies detection was developed based on IBM SPSS Modeler and is used to analyze SNMP data of the router. Investigation of the traffic anomalies was done using three classification methods and different sets of the learning data. Based on the results of investigation it was determined that C5.1 decision tree method has the largest accuracy and performance and can be successfully used for identification of the network traffic anomalies. Straipsnyje nagrinėjama kompiuterių tinklo srauto anomalijų atpažinimo problema. Apžvelgiami kompiuterių tinklų anomalijų aptikimo metodai bei aptariami jų privalumai ir trūkumai. Naudojant IBM SPSS Modeler programų paketą sudarytas nagrinėjamo tinklo srauto anomalijų atpažinimo modelis, pritaikytas SNMP protokolu pagrįstiems maršruto parinktuvo duomenims apdoroti. Pagal tris klasifikavimo metodus ir skirtingus mokymui skirtus duomenų rinkinius atlikti skaičiavimai tinklo anomalijoms identifikuoti. Palyginant gautus rezultatus nustatyta, kad C5.1 sprendimo medžio algoritmas yra tiksliausias ir sparčiausias, todėl ir tinkamiausias tinklo srauto anomalijoms atpažinti.

Rancang Bangun Aplikasi Sistem Pakar untuk Menangani Masalah Kecantikan pada Wajah Menggunakan Metode Decision Tree

2014 ◽  
Vol 6 (1) ◽  
pp. 9-14
Author(s):  
Stefanie Sirapanji ◽  
Seng Hansun
Keyword(s):  
Decision Tree ◽  
Uneven Distribution ◽  
Dry Skin ◽  
Average Accuracy ◽  
Accuracy Level ◽  
Index Terms ◽  
Decision Tree Method ◽  
Tree Method

Beauty is a precious asset for everyone. Everyone wants to have a healthy face. Unfortunately, there are always those problems that pops out on its own. For example, acnes, freckles, wrinkles, dull, oily and dry skin. Therefore, nowadays, there are a lot of beauty clinics available to help those who wants to solve their beauty troubles. But, not everyone can enjoy the facilities of those beauty clinics, for example those in the suburbs. The uneven distribution of doctors and the expensive cost of treatments are some of the reasons. In this research, the system that could help the patients to find the solution of their beauty problems is built. The decision tree method is used to take decision based on the shown schematic. Based on the system’s experiment, the average accuracy level hits 100%. Index Terms–Acnes, Decision Tree, Dry Skin, Dull, Facial Problems, Freckles, Wrinkles, Oily Skin, Eexpert System.

Marketing Model Investigation of Cable Television Service Based on BP Neural Network and Decision Tree

2013 ◽  
Vol 774-776 ◽  
pp. 1757-1761
Author(s):  
Bing Xiang Liu ◽  
Xu Dong Wu ◽  
Ying Xi Li ◽  
Xie Wei Wang
Keyword(s):  
Neural Network ◽  
Decision Tree ◽  
Bp Neural Network ◽  
Cable Television ◽  
Model Building ◽  
Television System ◽  
Marketing Model ◽  
Television Service ◽  
Decision Tree Method ◽  
Tree Method

This paper takes more than four hundred records of some cable television system for example, makes data mining according to users data record, uses BP neural network and decision tree method respectively to have model building and finds the best model fits for users to order press service. The results of the experiment validate the methods feasibility and validity.

Data Mining for ERW Welded Tube Scheduling Rules Based on Decision Tree

2011 ◽  
Vol 403-408 ◽  
pp. 1804-1807
Author(s):  
Ning Zhao ◽  
Shao Hua Dong ◽  
Qing Tian
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Arc Welding ◽  
Data Cleaning ◽  
Data Extraction ◽  
Electric Arc ◽  
Welded Tube ◽  
Electric Arc Welding ◽  
Decision Tree Method ◽  
Tree Method

In order to optimize electric- arc welding （ERW） welded tube scheduling , the paper introduces data cleaning, data extraction and transformation in detail and defines the datasets of sample attribute, which is based on analysis of production process of ERW welded tube. Furthermore, Decision-Tree method is adopted to achieve data mining and summarize scheduling rules which are validated by an example.

scholarly journals Penerapan Metode Klasifikasi Decision Tree Pada Status Gizi Balita Di Kabupaten Simalungun

2020 ◽  
Vol 1 (2) ◽  
pp. 68-72
Author(s):  
Hananda Hafizan ◽  
Anggita Nadia Putri
Keyword(s):  
Decision Tree ◽  
Nutritional Status ◽  
Public Health Service ◽  
Children Under Five ◽  
Under Five ◽  
C4.5 Algorithm ◽  
Decision Tree Method ◽  
Nutritional Status Of Children ◽  
Tree Method

One of the health problems in Indonesia is the problem of nutritional status of children under five years. Cases of malnutrition are not only a family problem, but also a state problem. The nutritional status of children under five years can be assessed by measuring the human body known as "Anthropometry". To be able to carry out anthropometric examinations and measurements in order to find out the nutritional status of children under five, they can go to public health service places such as the Posyandu. We went to the KENANGA Posyandu located in Wonorejo, Kerasaan sub-district, Simalungun district. The purpose of this study will be to test the model for the classification of nutritional status of children under the WHO-2005 reference standard by utilizing data mining techniques using the Decision Tree method C4.5 Algorithm.

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