Eko Arip Winanto
Universiti Teknologi Malaysia
Deep learningProof-of-work systemProof-of-stakeSignature (logic)Artificial intelligenceHeterogeneous networkReliability (computer networking)Set (abstract data type)Element (category theory)Pattern recognitionNetwork topologyPrincipal component analysisExtension (predicate logic)BlockchainNode (computer science)Consensus algorithmIdentification methodsComputer networkTestbedIntrusion detection systemComputer scienceNode (networking)Component (UML)Feature extractionEvent (computing)Object (computer science)Internet of ThingsDisk formattingWireless ad hoc networkRobustness (computer science)
6Publications
1H-index
1Citations
Publications 6
Newest
#2Eko Arip Winanto (UTM: Universiti Teknologi Malaysia)H-Index: 1
Last. Rahmat Budiarto (Al Baha University)H-Index: 13
view all 9 authors...
Heterogeneous network is one of the challenges that must be overcome in Internet of Thing Intrusion Detection System (IoT IDS). The difficulty of the IDS significantly is caused by various devices, protocols, and services, that make the network becomes complex and difficult to monitor. Deep learning is one algorithm for classifying data with high accuracy. This research work incorporated Deep Learning into IDS for IoT heterogeneous networks. There are two concerns on IDS with deep learning in he...
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#1Sharipuddin Sharipuddin (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...
The difficulty of the intrusion detection system in heterogeneous networks is significantly affected by devices, protocols, and services, thus the network becomes complex and difficult to identify. Deep learning is one algorithm that can classify data with high accuracy. In this research, we proposed deep learning to intrusion detection system identification methods in heterogeneous networks to increase detection accuracy. In this paper, we provide an overview of the proposed algorithm, with an ...
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#1Eko Arip Winanto (UTM: Universiti Teknologi Malaysia)H-Index: 1
#2Mohd. Yazid Idris (UTM: Universiti Teknologi Malaysia)H-Index: 7
Last. Mohammad Sulkhan Nurfatih (UTM: Universiti Teknologi Malaysia)
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Signature-based Collaborative Intrusion Detection System (CIDS) is highly depends on the reliability of nodes to provide IDS attack signatures. Each node in the network is responsible to provide new attack signature to be shared with other node. There are two problems exist in CIDS highlighted in this paper, first is to provide data consistency and second is to maintain trust among the nodes while sharing the attack signatures. Recently, researcher find that blockchain has a great potential to s...
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#1Muhammad Sulkhan Nurfatih (UTM: Universiti Teknologi Malaysia)
#2Mohd. Yazid Idris (UTM: Universiti Teknologi Malaysia)H-Index: 7
Last. Eko Arip Winanto (UTM: Universiti Teknologi Malaysia)H-Index: 1
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Vehicular Ad-hoc Networks (VANETs) presents smart transport that is capable of processing data and can self-organize for each vehicle. However, there have been security issues such as communication breakdowns between vehicles and information trust. Therefore, the trust model becomes an essential element in overcoming this problem. Various trust models have been suggested in the literature, including the model that utilizing consensus algorithm in the blockchain. This paper proposes an extension ...
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#1Eko Arip Winanto (UTM: Universiti Teknologi Malaysia)H-Index: 1
#2Mohd. Yazid Idris (UTM: Universiti Teknologi Malaysia)H-Index: 7
Last. Sharipuddin (Sriwijaya University)H-Index: 1
view all 5 authors...
Signature-based Collaborative Intrusion Detection System (CIDS) deeply depends on the reliability of nodes to produce attack signatures. Each node in the network is responsible to produce a new attack signature to be distributed with other nodes. There is an issue that exists in CIDS highlighted in this paper, it is to maintain trust between the nodes while distributing the attack signatures. Recently, researchers found that blockchain has great potential to solve those problems. A consensus alg...
Source
#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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