Deris Stiawan
Sriwijaya University
The InternetOperating systemMachine learningData miningEngineeringFeature selectionArtificial intelligenceNetwork packetComputer networkIntrusion detection systemComputer securityDenial-of-service attackComputer scienceNaive Bayes classifierFeature extraction
141Publications
10H-index
247Citations
Publications 172
Newest
#2Deris StiawanH-Index: 10
Last. Ahmad HeryantoH-Index: 3
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Remote Access Trojans (RATs) are a serious problem that needs to be resolved. RATs run silently in the background making them difficult to detect by users. Intrusion Detection and Prevention System (IDPS) is usually applied to solved this. Many NIDPS devices have been distributed from various vendors, but these devices are difficult to reach Small Office and Home Office (SOHO) because they have quite expensive selling price. To solve this problem, researchers designed IDPS on a Small Board Compu...
#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
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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...
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#2Deris StiawanH-Index: 10
Last. Ahmad HeryantoH-Index: 3
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Intrusion Prevention System (IPS) is an approach used to build a computer security system that is more advanced than the Intrusion Detection System (IDS), because this IPS can do more than just analyze traffic / logs and generate alerts. IPS responds to detected intrusion packets and will block malicious activity on the network. The dataset used is NSL - KDD which will be detected by IDS Snort so that it gets an attack pattern to perform the detection process using the support vector machine met...
#2Deris StiawanH-Index: 10
Last. Ahmad HeryantoH-Index: 3
view all 3 authors...
Intrusion detection system (IDS) which is a system for detecting traffic in a network, but the weakness of this IDS can only detect and provide alerts without responding if there is an attack packet. The system that detects and responds to network traffic is called an intrusion prevention system (IPS), which is a system that is capable of giving actions to deny or allow a packet passing through the network traffic. Remote to Local (R2L) is an intrusion that aims to access the system that is the ...
#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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#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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#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...
Source
#2Deris StiawanH-Index: 10
Last. Sarmayanta SembiringH-Index: 1
view all 3 authors...
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...
Email spam is a topic of problem that will continue to increase because it is easy and cheap to send email, which can be annoying and time-consuming for users. For that reason, the classification of spam emails is still challenging because there are still a lot of spam emails. This research was conducted on two email spam datasets, namely the Spambase dataset obtained from UCI Machine Learning, and the Emails dataset obtained from Kaggle. Spam classification is done using the Decision Tree algor...
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