Kurniabudi
Sriwijaya University
Automatic identification and data captureData pre-processingAlgorithmCommunications protocolData miningFeature selectionEncryptionArtificial intelligenceReliability (computer networking)Random forestData analysisSet (abstract data type)Pattern recognitionComputational complexity theoryTopology (electrical circuits)Network topologyKey (cryptography)Information gain ratioWireless sensor networkPrincipal component analysisTraffic analysisRobust analysisDetection performanceComputer networkSystems designTestbedBayesian networkPreprocessorComplex networkIntrusion detection systemComputer scienceComponent (UML)Naive Bayes classifierC4.5 algorithmFeature extractionWirelessAnomaly detectionBig dataAnalyticsReal-time computingUnsupervised learningDecision treeParticle swarm optimizationDisk formattingProtocol (object-oriented programming)
15Publications
2H-index
63Citations
Publications 7
Newest
#1Deris StiawanH-Index: 10
#2Ahmad HeryantoH-Index: 3
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...
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#1Kurniabudi (Sriwijaya University)H-Index: 2
Last. Rahmat Budiarto (Al Baha University)H-Index: 13
view all 7 authors...
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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#1Sharipuddin (Sriwijaya University)H-Index: 1
#2Benni Purnama (Sriwijaya University)H-Index: 3
Last. Rahmat Budiarto (Al Baha University)H-Index: 13
view all 8 authors...
Feature extraction solves the problem of finding the most efficient and comprehensive set of features. A Principle Component Analysis (PCA) feature extraction algorithm is applied to optimize the effectiveness of feature extraction to build an effective intrusion detection method. This paper uses the Principal Components Analysis (PCA) for features extraction on intrusion detection system with the aim to improve the accuracy and precision of the detection. The impact of features extraction to at...
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#1KurniabudiH-Index: 2
#2Deris StiawanH-Index: 10
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...
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Oct 1, 2018 in ICEE (International Conference on Electrical Engineering)
#1SharipuddinH-Index: 1
#2KurniabudiH-Index: 2
Last. Rahmat Budiarto (Al Baha University)H-Index: 13
view all 9 authors...
This study presents the testing of several devices (sensors) in obtaining sensor performance, there are several experiments and evaluations of the results obtained in the topology. Each sensor must be able to provide some results in the form of accuracy, reliability, range, and resolution. The accuracy and reliability have very important role in producing accurate data. With several explanations and analysis, it is expected to produce a reference for advanced development and policies making in t...
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Oct 1, 2018 in ICEE (International Conference on Electrical Engineering)
#1KurniabudiH-Index: 2
#2Benni PurnamaH-Index: 3
Last. Rahmat Budiarto (Al Baha University)H-Index: 13
view all 6 authors...
A robust increasing on smart sensors in Internet of Thing (IoT) results huge and heterogenous data and becomes a challenge in data prepocessing and analysis for anomaly detection. The lack of IoT publicly available dataset is one issue in anomaly detection research. To resolve that problem, a testbed topology is proposed in this research. In addition, a high-dimensionality data analysis faces a computational complexity. The purpose of this study is to presents a global framework for anomaly dete...
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Oct 1, 2018 in ICEE (International Conference on Electrical Engineering)
#1Benni PurnamaH-Index: 3
#2SharipuddinH-Index: 1
Last. Darmawijoyo HanapiH-Index: 1
view all 6 authors...
Internet of Things (IoT) networks operators may not be fully aware whether each IoT device in their network is functioning safe enough from cyber-attacks. This paper develops an IoT traffic dataset with the purpose of of network traffic analytics to characterize IoT devices, including their typical behaviour mode. We set up an IoT environment/testbed consists of several sensors/nodes and uses Zigbee communication protocol to collect and synthesize traffic traces. Normal dataset and anomaly/attac...
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