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Fujiama Diapoldo Silalahi
Universitas Sains Dan Teknologi Komputer
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Social Sciences Other

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Journal : Journal of Technology Informatics and Engineering

 1 
Enhancing Performance Using New Hybrid Intrusion Detection System Candra Supriadi; Charli Sitinjak; Fujiama Diapoldo Silalahi; Nia Dharma Pertiwi; Sigit Umar Anggono
Journal of Technology Informatics and Engineering Vol 1 No 2 (2022): Agustus: Journal of Technology Informatics and Engineering
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v1i1.134

Abstract

Intrusion Detection Systems (IDS) are an efficient defense against network attacks as well as host attacks as they allow network/host administrators to detect any policy violations. However, traditional IDS are vulnerable and unreliable for new malicious and genuine attacks. In other case, it is also inefficient to analyze large amount of data such as possibility logs. Furthermore, for typical OS, there are a lot of false positives and false negatives. There are some techniques to increase the quality and result of IDS where data mining is one of technique that is important to mining the information that useful from a large amount of data which noisy and random. The purpose of this study is to combine three technique of data mining to reduce overhead and to improve efficiency in intrusion detection system (IDS). The combination of clustering (Hierarchical) and two categories (C5, CHAID) is proposed in this study. The designed IDS is evaluated against the KDD'99 standard Data set (Knowledge Discovery and Data Mining), which is used to evaluate the efficacy of intrusion detection systems. The suggested system can detect intrusions and categorize them into four categories: probe, DoS, U2R (User to Root), and R2L (Remote to Local). The good performance of IDS in case of accuracy and efficiency was the result of this study.
CREDENTIAL ANALYSIS FOR SECURITY CONFIGURATION ON CUSTOM ANDROID ROM Joseph Teguh Santoso; Fujiama Diapoldo Silalahi; Laksamana Rajendra Haidar
Journal of Technology Informatics and Engineering Vol 1 No 3 (2022): Desember: Journal of Technology Informatics and Engineering
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v1i3.149

Abstract

Android is an operating system with open source and consists of several layers, with the different layers its duties and responsibilities. Various parties in the customization chain such as device vendors such as Samsung, Xiaomi, Oppo, Huawei, and others, operators such as Telkomsel, Smartfren, XL, etc., and hardware manufacturers can customize one or more layers to adapt devices for different purposes, such as supporting specific hardware and providing different interfaces and services. The purpose of this study was to investigate systematically for any inconsistencies that arose as a result of the processes involved in this study and to assess their various security implications. This research runs DroidDiff to perform a substantial-balance diverse investigation on images collected by the analytical methodology. DroidDiff found a lot of differences when it comes to the selected features. The method used in this study is the method of five differential analysis algorithms. As a result, by comparing the security configurations of similar figures, important security changes that could be accidentally introduced during customization can be found. The results show that DroidDiff can be used by vendors to check the configuration of various security features in a given image. DroidDiff will extract those features from the image, and compare them to other image configuration sets, then DroidDiff will flag the inconsistent ones for further investigation by vendors who have the source code and tools to check their effect. For future work, improvements to DroidDiff to more accurately detect risky inconsistencies are highly recommended. Improving DroidDiff will help reduce the number of false positives and determine risky configurations more accurately.
Co-Authors Budi Hartono Candra Supriadi Candra Supriadi Danang, Danang Daniel Rudjiono Dian Noor Hamami Firman Murtadlo Galeh Septiar Pontang Hendri Rasminto Indrawan Nagasus Iwan Koerniawan Jarot Dian Joseph Teguh Santoso Khoirur Rozikin Laksamana Rajendra Haidar Moh Muthohir Muhammad Sholikhan Mukhoyyarotul Jannah Nandito Putra Prabawa Nia Dharma Pertiwi Nuris Dwi Setiawan Setiyo Prihatmoko Sigit Umar Anggono Sitinjak, Charli Sumaryanto Yogiswara Yogiswara