detection system regarding to attack detection on
TRANSCRIPT
Machine Learning-BasedDistributed Denial of ServiceAttack Detection on Intrusion
Detection System Regarding toFeature Selection
by Arif Wirawan
Submission date: 15-Feb-2020 04:49AM (UTC-0500)Submission ID: 1239759951File name: BUSINTA_Template_-_naskah_-_translate.docx (337.48K)Word count: 3080Character count: 16373
19%SIMILARITY INDEX
11%INTERNET SOURCES
15%PUBLICATIONS
16%STUDENT PAPERS
1 3%
2 2%
3 2%
4 1%
5 1%
6 1%
7
Machine Learning-Based Distributed Denial of Service AttackDetection on Intrusion Detection System Regarding to FeatureSelectionORIGINALITY REPORT
PRIMARY SOURCES
Submitted to Universitas Muslim IndonesiaStudent Paper
Devina Gilar Fitri Ayu Sumardi, TutiPurwaningsih. "Spatial regression analysis fordiscovering quality living index (QLI) in Asia",Bulletin of Social Informatics Theory andApplication, 2018Publication
Submitted to RMIT UniversityStudent Paper
Submitted to Universiti Malaysia SarawakStudent Paper
Submitted to University of SunderlandStudent Paper
www.ijitee.orgInternet Source
Submitted to University of Pretoria
1%
8 1%
9 1%
10 <1%
11 <1%
12 <1%
Student Paper
M. R. Gauthama Raman, Nivethitha Somu,Sahruday Jagarapu, Tina Manghnani et al. "Anefficient intrusion detection technique based onsupport vector machine and improved binarygravitational search algorithm", ArtificialIntelligence Review, 2019Publication
Submitted to Stockhom University & The RoyalInstitute of TechnologyStudent Paper
Imam Riadi, Arif Wirawan, Sunardi -. "NetworkPacket Classification using Neural Networkbased on Training Function and Hidden LayerNeuron Number Variation", International Journalof Advanced Computer Science andApplications, 2017Publication
Mohamed Idhammad, Karim Afdel, MustaphaBelouch. "Semi-supervised machine learningapproach for DDoS detection", AppliedIntelligence, 2018Publication
Submitted to University of StrathclydeStudent Paper
13 <1%
14 <1%
15 <1%
16 <1%
17 <1%
18 <1%
Herman R.A. Talompo, Adang Suwandi Ahmad,Yudi S. Gondokaryono, Sarwono Sutikno."NAIDS design using ChiMIC-KGS", 2017International Symposium on Electronics andSmart Devices (ISESD), 2017Publication
www.tandfonline.comInternet Source
Nickolaos Koroniotis, Nour Moustafa, ElenaSitnikova, Jill Slay. "Chapter 3 TowardsDeveloping Network Forensic Mechanism forBotnet Activities in the IoT Based on MachineLearning Techniques", Springer Science andBusiness Media LLC, 2018Publication
link.springer.comInternet Source
Submitted to George Washington UniversityStudent Paper
Malek Al-Zewairi, Sufyan Almajali, ArafatAwajan. "Experimental Evaluation of a Multi-layer Feed-Forward Artificial Neural NetworkClassifier for Network Intrusion DetectionSystem", 2017 International Conference on NewTrends in Computing Sciences (ICTCS), 2017Publication
19 <1%
20 <1%
21 <1%
22 <1%
23 <1%
"Web, Artificial Intelligence and NetworkApplications", Springer Science and BusinessMedia LLC, 2019Publication
Florian Gottwalt, Elizabeth Chang, TharamDillon. "CorrCorr: A feature selection method formultivariate correlation network anomalydetection techniques", Computers & Security,2019Publication
Arif Wirawan Muhammad, Ginanjar WiroSasmito, Imam Riadi. "Colorectal PolypDetection Using Feedforward Neural Networkwith Image Feature Selection", 2018International Symposium on AdvancedIntelligent Informatics (SAIN), 2018Publication
Amin Karami. "An Anomaly-based IntrusionDetection System in Presence of BenignOutliers with Visualization Capabilities", ExpertSystems with Applications, 2018Publication
Ilyas Benmessahel, Kun Xie, Mouna Chellal. "Anew evolutionary neural networks based onintrusion detection systems using multiverseoptimization", Applied Intelligence, 2017Publication
24 <1%
25 <1%
26 <1%
27 <1%
28 <1%
29 <1%
Ahmad Azhari, Murein Miksa Mardhia. "Principalcomponent analysis implementation forbrainwave signal reduction based on cognitiveactivity", International Journal of Advances inIntelligent Informatics, 2017Publication
pubs.ascee.orgInternet Source
S. Devaraju, S. Ramakrishnan. "Detection ofAttacks for IDS using Association Rule MiningAlgorithm", IETE Journal of Research, 2015Publication
Myo Myint Oo, Sinchai Kamolphiwong,Thossaporn Kamolphiwong, SangsureeVasupongayya. "Advanced Support VectorMachine- (ASVM-) Based Detection forDistributed Denial of Service (DDoS) Attack onSoftware Defined Networking (SDN)", Journal ofComputer Networks and Communications, 2019Publication
Adel Binbusayyis, Thavavel Vaiyapuri."Identifying and Benchmarking Key Features forCyber Intrusion Detection: An EnsembleApproach", IEEE Access, 2019Publication
E.Y. Chen, A. Yonezawa. "Practical techniquesfor defending against DDoS attacks", The 3rd
30 <1%
31 <1%
32 <1%
33 <1%
34 <1%
Exclude quotes On Exclude matches Off
ACS/IEEE International ConferenceonComputer Systems and Applications, 2005.,2005Publication
Submitted to Kennesaw State UniversityStudent Paper
Submitted to Sheffield Hallam UniversityStudent Paper
ZONE-CHING LIN, Q.Y. LIU. "A neural network-based algorithm that searches for the measuringpoints of a rule surface", IIE Transactions, 2000Publication
"Artificial Intelligence and EvolutionaryComputations in Engineering Systems",Springer Science and Business Media LLC,2020Publication
Anton Yudhana, Imam Riadi, Faizin Ridho."DDoS Classification Using Neural Network andNaïve Bayes Methods for Network Forensics",International Journal of Advanced ComputerScience and Applications, 2018Publication
Exclude bibliography On