Deris Stiawan
Sriwijaya University
The InternetOperating systemMachine learningData miningEngineeringFeature selectionArtificial intelligenceNetwork packetComputer networkIntrusion detection systemComputer securityDenial-of-service attackComputer scienceNaive Bayes classifierFeature extraction
141Publications
9H-index
247Citations
Publications 83
Newest
#1Deris StiawanH-Index: 9
#2Ahmad HeryantoH-Index: 2
Last. Rahmat BudiartoH-Index: 13
view all 10 authors...
Intrusion Detection System is yet an interesting research topic. With a very large amount of traffic in real-time networks, feature selection techniques that are effectively able to find important and relevant features are required. Hence, the most important and relevant set of features is the key to improve the performance of intrusion detection system. This study aims to find the best relevant selected features that can be used as important features in a new IDS dataset. To achieve the aim, an...
2 CitationsSource
#1Kurniabudi (Sriwijaya University)H-Index: 3
Last. Rahmat Budiarto (Al Baha University)H-Index: 13
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The feature selection techniques are used to find the most important and relevant features in a dataset. Therefore, in this study feature selection technique was used to improve the performance of Anomaly Detection. Many feature selection techniques have been developed and implemented on the NSL-KDD dataset. However, with the rapid growth of traffic on a network where more applications, devices, and protocols participate, the traffic data is complex and heterogeneous contribute to security issue...
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#1Susanto (Sriwijaya University)
#3M. Agus Syamsul Arifin (Sriwijaya University)
Last. Rahmat Budiarto (Al Baha University)H-Index: 13
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Botnet is one of the threats to internet network security-Botmaster in carrying out attacks on the network by relying on communication on network traffic. Internet of Things (IoT) network infrastructure consists of devices that are inexpensive, low-power, always-on, always connected to the network, and are inconspicuous and have ubiquity and inconspicuousness characteristics so that these characteristics make IoT devices an attractive target for botnet malware attacks. In identifying whether pac...
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#2Deris StiawanH-Index: 9
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This final project aims to create a system that can detect cyber attacks on the national indexation server with notification rotater lights. NodeMCU ESP8266 is used as a microcontroller in this final project. 106 data samples with the type of brute force attack were used for system testing. And the SdCard module is used to store test data samples and test results, which are connected to the ESP8266 NodeMCU. As a result, the system can detect attacks with an accuracy rate of 100% and an error rat...
#1Deris StiawanH-Index: 9
Last. Rahmat BudiartoH-Index: 13
view all 6 authors...
Granblue Fantasy is one of Role Playing Games (RPG). It’s a video role-playing game developed by Cygames. This research to observes the Granblue Fantasy Game. The purpose is to analyze the traffic data of the Granblue Fantasy to find the pattern using Deep Packet Inspection (DPI), Capturing the Data Traffic, Feature Extraction Process and Visualize the Pattern. The Pattern are Gacha, Solo Raid, Casino and Multiraid. This research demonstrate that Multiraid battle has more data than other pattern...
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#2Dian Palupi RiniH-Index: 4
Last. Deris StiawanH-Index: 9
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Distributed Denial of Service (DDoS) is one of the most powerful threat on the internet. DDoS attacks target websites and online services. Taking knowledge from DDoS attack data with machine learning to learn the pattern is very important to prevent and handle such attacks, one of them is by classification using the Naive Bayes method. To improve the performance of Naive Bayes results, it can be done by combining them using Artificial Bee Colony during the classification process for selecting DD...
#2Dian Palupi RiniH-Index: 4
Last. Deris StiawanH-Index: 9
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DDoS is one of dangerous internet / cyber attacks. One of solution for overcoming the problem with identifying a traffic network wheter if it contains DDoS attack or not. Identification requires a lot of data for recognizing the pattern of DDoS attack so that it can be prevented as soon as possible. But, the traffic network it self has contain a lot of data per seconds. Therefore, a classification algorithm that can process a lot of data at one time is required to solve the problem, one of them ...
#2Dian Palupi RiniH-Index: 4
Last. Deris StiawanH-Index: 9
view all 3 authors...
DDoS is one type of internet attack that can threaten internet users, especially web application users, DDoS attacks can cause a server to malfunction on a network, which is caused by the large amount of bandwidth traffic that is launched by an attacker through DDoS. Therefore, we need a way to identify a network traffic, that is by carrying out a classification process on a network traffic data to find out whether it is an attack or not. because the amount of network traffic data is very much p...
#1KurniabudiH-Index: 3
#2Deris StiawanH-Index: 9
Last. Rahmat BudiartoH-Index: 13
view all 6 authors...
Feature selection (FS) is one of the important tasks of data preprocessing in data analytics. The data with a large number of features will affect the computational complexity, increase a huge amount of resource usage and time consumption for data analytics. The objective of this study is to analyze relevant and significant features of huge network traffic to be used to improve the accuracy of traffic anomaly detection and to decrease its execution time. Information Gain is the most feature sele...
31 CitationsSource
#1Nur Sholihah Zaini (Universiti Malaysia Pahang)
#2Deris StiawanH-Index: 9
Last. Tole Sutikno (Universitas Ahmad Dahlan)H-Index: 15
view all 7 authors...
The increasing development of the Internet, more and more applications are put into websites can be directly accessed through the network. This development has attracted an attacker with phishing websites to compromise computer systems. Several solutions have been proposed to detect a phishing attack. However, there still room for improvement to tackle this phishing threat. This paper aims to investigate and evaluate the effectiveness of machine learning approach in the classification of phishin...
2 CitationsSource