Mohd. Yazid Idris
Universiti Teknologi Malaysia
The InternetAlgorithmData miningEngineeringArtificial intelligenceIntrusionNetwork packetPattern recognitionIntrusion prevention systemBlockchainConsensus algorithmComputer networkIntrusion detection systemComputer securityComputer scienceComponent (UML)Software developmentEvent (computing)Feature (computer vision)Anomaly detectionProcess (computing)
52Publications
8H-index
149Citations
Publications 55
Newest
#1Deris Stiawan (Sriwijaya University)H-Index: 9
#2Somame Morianus Daely (Sriwijaya University)
Last. Rahmat Budiarto (Al Baha University)H-Index: 13
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Ransomware is a malware that represents a serious threat to a user’s information privacy. By investigating howransomware works, we may be able to recognise its atomic behaviour. In return, we will be able to detect theransomware at an earlier stage with better accuracy. In this paper, we propose Control Flow Graph (CFG) asan extracting opcode behaviour technique, combined with 4-gram (sequence of 4 “words”) to extract opcodesequence to be incorporated into Trojan Ransomware detection method usin...
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#2Eko Arip Winanto (UTM: Universiti Teknologi Malaysia)H-Index: 1
Last. Rahmat Budiarto (Al Baha University)H-Index: 13
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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
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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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#1Deris Stiawan (Sriwijaya University)H-Index: 9
#2Meilinda Eka Suryani (Sriwijaya University)
Last. Rahmat Budiarto (Al Baha University)H-Index: 13
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Security is the main challenge in Internet of Things (IoT) systems. The devices on the IoT networks are very heterogeneous, many of them have limited resources, and they are connected globally, which makes the IoT much more challenging to secure than other types of networks. Denial of service (DoS) is the most popular method used to attack IoT networks, either by flooding services or crashing services. Intrusion detection system (IDS) is one of countermeasures for DoS attack. Unfortunately, the ...
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The growth in internet traffic volume presents a new issue in anomaly detection, one of which is the high data dimension. The feature selection technique has been proven to be able to solve the problem of high data dimension by producing relevant features. On the other hand, high-class imbalance is a problem in feature selection. In this study, two feature selection approaches are proposed that are able to produce the most ideal features in the high-class imbalanced dataset. CICIDS-2017 is a rel...
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Supervisory control and data acquisition (SCADA) has an important role in communication between devices in strategic industries such as power plant grid/network. Besides, the SCADA system is now open to any external heterogeneous networks to facilitate monitoring of industrial equipment, but this causes a new vulnerability in the SCADA network system. Any disruption on the SCADA system will give rise to a dangerous impact on industrial devices. Therefore, deep research and development of reliabl...
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#1Eko Arip Winanto (UTM: Universiti Teknologi Malaysia)H-Index: 1
#2Mohd. Yazid Idris (UTM: Universiti Teknologi Malaysia)H-Index: 8
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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Malware may disrupt the Internet of Thing (IoT) system/network when it resides in the network, or even harm the network operation. Therefore, malware detection in the IoT system/network becomes an important issue. Research works related to the development of IoT malware detection have been carried out with various methods and algorithms to increase detection accuracy. The majority of papers on malware literature studies discuss mobile networks, and very few consider malware on IoT networks. This...
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#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
#1Muhammad Sulkhan Nurfatih (UTM: Universiti Teknologi Malaysia)
#2Mohd. Yazid Idris (UTM: Universiti Teknologi Malaysia)H-Index: 8
Last. Eko Arip Winanto (UTM: Universiti Teknologi Malaysia)H-Index: 1
view all 4 authors...
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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