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All Journal PROSIDING SEMINAR NASIONAL Kompak : Jurnal Ilmiah Komputerisasi Akuntansi E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis Elkom: Jurnal Elektronika dan Komputer JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Informatika Upgris Wikrama Parahita : Jurnal Pengabdian Masyarakat JMM (Jurnal Masyarakat Mandiri) Equilibria Pendidikan : Jurnal Ilmiah Pendidikan Ekonomi JURNAL NUSANTARA APLIKASI MANAJEMEN BISNIS Social, Humanities, and Educational Studies (SHEs): Conference Series Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknik Informatika (JUTIF) Community Empowerment Journal of Soft Computing Exploration Bima Abdi: Jurnal Pengabdian Masyarakat MANAJEMEN Journal of Engineering, Electrical and Informatics (JEEI) Jurnal Manajemen, Bisnis dan Kewirausahaan Lamahu: Jurnal Pengabdian Masyarakat Terintegrasi Journal Online Manajemen ELPEI (JOMEL) Jurnal Publikasi Ilmu Komputer dan Multimedia Jurnal Manajemen Informatika & Teknologi Jurnal Publikasi Manajemen Informatika (JUPUMI) Jurnal Publikasi Teknik Informatika (JUPTI) Journal of Technology Informatics and Engineering Jurnal Pengabdian Masyarakat dan Riset Pendidikan Andragogi Jurnal Pendidikan dan Pembelajaran Pemuliaan Keadilan Journal of Information Engineering and Technology Studies in Social Sciences and Humanities JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Journal of Engineering, Electrical and Informatics Mavis: Jurnal Desain Komunikasi Visual Jurnal Manajemen, Bisnis dan Kewirausahaan
Zaenal Mustofa
Universitas Negeri Yogyakarta
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Public Health Social Sciences Other

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Journal : Journal of Technology Informatics and Engineering

 1 
ADVANCED MALICIOUS SOFTWARE DETECTION USING DNN Sulartopo Sulartopo; Dani Sasmoko; Zaenal Mustofa; Arsito Ari Kuncoro
Journal of Technology Informatics and Engineering Vol 1 No 1 (2022): April: 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.v1i1.144

Abstract

The special component of malicious software analysis is advanced malicious software analysis which implicates interested the main framework of malicious software that can be executed after executing it and aggressive malicious software investigation depend on inquisitive of the practice of malicious software after running it in a composed habitat. Advanced malicious software analysis is usually performed by contemporary anti-malicious software operating systems using signature-based analysis. The purpose of this research is to propose also decide a DNN for the progressive identification of portable files to study the features of portable executable malicious software to minimize the occurrence of distorted likeness when aware of advanced malicious software. The model proposed in this study is a NN with a Dropout model contrary to a resolution tree model to examine how well it performs in detecting real malicious PE files. Setup-skeptic methods are used to extract features from files. The dataset is used to train the proposed approach and measure outcomes by alternative common malicious software datasets. The results from this study illustrate that the use of simple DNNs to study PE vector elements is not only efficient but more fewer system comprehensive than the traditional interested disclosure approach. The model proposed in this study achieves an A-UC of ninety-nine point eight with ninety accurate specifics at one percent inaccurate specific on the R-OC curve. For shows that this model has the potential to complement or replace conventional anti-malicious software operating systems so for future research, it is proposed to implement this model practically.
ADVANCED MALICIOUS SOFTWARE DETECTION USING DNN Sulartopo Sulartopo; Dani Sasmoko; Zaenal Mustofa; Arsito Ari Kuncoro
Journal of Technology Informatics and Engineering Vol 1 No 1 (2022): April: Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v1i1.144

Abstract

The special component of malicious software analysis is advanced malicious software analysis which implicates interested the main framework of malicious software that can be executed after executing it and aggressive malicious software investigation depend on inquisitive of the practice of malicious software after running it in a composed habitat. Advanced malicious software analysis is usually performed by contemporary anti-malicious software operating systems using signature-based analysis. The purpose of this research is to propose also decide a DNN for the progressive identification of portable files to study the features of portable executable malicious software to minimize the occurrence of distorted likeness when aware of advanced malicious software. The model proposed in this study is a NN with a Dropout model contrary to a resolution tree model to examine how well it performs in detecting real malicious PE files. Setup-skeptic methods are used to extract features from files. The dataset is used to train the proposed approach and measure outcomes by alternative common malicious software datasets. The results from this study illustrate that the use of simple DNNs to study PE vector elements is not only efficient but more fewer system comprehensive than the traditional interested disclosure approach. The model proposed in this study achieves an A-UC of ninety-nine point eight with ninety accurate specifics at one percent inaccurate specific on the R-OC curve. For shows that this model has the potential to complement or replace conventional anti-malicious software operating systems so for future research, it is proposed to implement this model practically.
ADVANCED MALICIOUS SOFTWARE DETECTION USING DNN Sulartopo Sulartopo; Dani Sasmoko; Zaenal Mustofa; Arsito Ari Kuncoro
Journal of Technology Informatics and Engineering Vol. 1 No. 1 (2022): April: Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v1i1.144

Abstract

The special component of malicious software analysis is advanced malicious software analysis which implicates interested the main framework of malicious software that can be executed after executing it and aggressive malicious software investigation depend on inquisitive of the practice of malicious software after running it in a composed habitat. Advanced malicious software analysis is usually performed by contemporary anti-malicious software operating systems using signature-based analysis. The purpose of this research is to propose also decide a DNN for the progressive identification of portable files to study the features of portable executable malicious software to minimize the occurrence of distorted likeness when aware of advanced malicious software. The model proposed in this study is a NN with a Dropout model contrary to a resolution tree model to examine how well it performs in detecting real malicious PE files. Setup-skeptic methods are used to extract features from files. The dataset is used to train the proposed approach and measure outcomes by alternative common malicious software datasets. The results from this study illustrate that the use of simple DNNs to study PE vector elements is not only efficient but more fewer system comprehensive than the traditional interested disclosure approach. The model proposed in this study achieves an A-UC of ninety-nine point eight with ninety accurate specifics at one percent inaccurate specific on the R-OC curve. For shows that this model has the potential to complement or replace conventional anti-malicious software operating systems so for future research, it is proposed to implement this model practically.
Co-Authors Achmad Faisal Abda’ Agus Qomaruddin Munir AGUS SUSILO ROMADHON Ahmad Ashifuddin Aqham Ahmad Asifuddin Ahmad Zakiy Ramadhan Al-Khawarizmi, Andi Hakim Annur Trihardiyanti Ardini, Fadhila Malasari Arie Atwa Magriyanti Aris Prio Agus Santoso Arsito Ari Kuncoro Arsito Ari Kuncoro Bachtiar Aziz Mulki Budi Hartono budi hartono Buntara Adi Purwanto Danang , Danang Danang Danang Danang, Danang Dani Sasmoko Dani Sasmoko Doni Marhab Eka Satria Wibawa Eko Siswanto Eko Siswanto Endang Sri Budi Herawati Fahrozi Ar-Ra’afi Febryantahanuji Febryantahanuji Firmansah, Firmansah Gita Amalia Hadi Yusuf Hadi Yusuf Haris Ihsanil Huda Ikka Rusmawardani Afsah Iman Saufik Suasana Ismarini Bekti Setiani Jozua Ferjanus Palandi Kun Mabruroh Lina Rahmawati Lukman Hakim Lupita Orisativa Aprilia Marhab, Doni Maryono, Dicky Maya Utami Dewi Miftahul Fuadi Mokhamad Iklil Mustofa Muhammad Nafis Muhammad Resa Arif Yudianto Muhammad Sholikhan Mumpuni, Sesya Dias Nadhir Fachrul Rozam Nova Nur Ramadhani Nur Rina Priyani Mirsa Nurkhamid, Nurkhamid Nurulloh, Ahmat Paulus Hartanto Prayogi, Arditya Priadi Surya Puput Mulyono Putri Avinda Rahman, Dzul Fadli Ratna Wardani Rina Arum Prastyanti Rinawan, Rangga Bayu Rini Rhubiyanti Riziq Anta Yahya Rizky Aji Prasetyo Rohman, M Aguts Rosita Dwi Widya Ningrum Sari, Maya Novita Sela Asyifa Dalila Setiyawan, Ramadhana singgih Prabowo Siswanto, Edy Siti Kholifah Siti Kholifah Somad, Mohamad Ali Sulartopo Sulartopo Sulartopo Sulartopo Sumaryanto Sumaryanto Sumaryanto, Sumaryanto Susilowati, Novi Tika Novita Sari Toni Wijanarko Adi Putra Triyanto Agung Praptono Wibowo Wahyu Efendy Yusuf Wahyu EY Widiatmoko, Mualwi Widiyan, Agung Purwa Wiwid Wahyudi Wulan Tri Puji Utami Yuni Astuti Yussi Anggraini Zakariah, Masduki