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Jurnal Institusi

Live Forensics Analysis Of Malware Identified Email Crimes To Increase Evidence Of Cyber Crime

Digital Zone: Jurnal Teknologi Informasi dan Komunikasi; Vol. 13 No. 2 (2022): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning, 2022DOI: 10.31849/digitalzone.v13i12.11570Copyright (c) 2022 Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Now days Email is the most important aplplication  on the internet, this make email one of the industry’s most targeted sector for commiting cyber crimes. Email phishing and spam not only harm many parties but also consumes a lot of networ...
Jurnal Institusi

Comparative Study of the Effect of Datasets and Machine Learning Algorithms for PDF Malware Detection

Digital Zone: Jurnal Teknologi Informasi dan Komunikasi; Vol. 15 No. 1 (2024): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi ; 80-93
Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning, 2024DOI: 10.31849/digitalzone.v15i1.19744Copyright (c) 2024 Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
This research presents an innovative approach to detecting malicious PDFs through machine learning algorithms, focusing on the expansion of the Evasive-PDFMal2022 dataset. The objective is to enhance the accuracy of detecting malicious PDFs by enrich...
Jurnal Institusi

Ransomware Attacks Threat Modeling Using Bayesian Network: Pemodelan Ancaman Serangan Ransomware Menggunakan Bayesian Network

Digital Zone: Jurnal Teknologi Informasi dan Komunikasi; Vol. 14 No. 1 (2023): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi ; 43-56
Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning, 2023DOI: 10.31849/digitalzone.v14i1.13788Copyright (c) 2023 Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Ransomware is a dangerous malware that blocks access to data through encryption, and it exploits device vulnerabilities to perform chain attacks from one system to another. This study results in modeling the threat of ransomware attacks using Bayesia...
Jurnal Institusi

Cyber Security Risks in the Rapid Development of Generative Artificial Intelligence: A Systematic Literature Review

ComniTech : Journal of Computational Intelligence and Informatics ; Vol. 1 No. 2 (2024): ComniTech : Journal of Computational Intelligence and Informatics; 57-66
Universitas Lancang Kuning, 2024Copyright (c) 2024 ComniTech : Journal of Computational Intelligence and Informatics
This study aims to identify the cybersecurity risks arising from the use of Generative Artificial Intelligence (GenAI). By employing a systematic literature review (SLR) method and following the PRISMA 2020 guidelines, this research systematically se...
PubMed

Towards a systematic description of the field using bibliometric analysis: malware evolution

Scientometrics
2021DOI: 10.1007/s11192-020-03834-6© Akadémiai Kiadó, Budapest, Hungary 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Malware is a blanket term for Trojan, viruses, spyware, worms, and other files that are purposely created to harm computers, mobile devices, or computer networks. Malware commonly steals, encrypts, damages, and causes a mess in these devices. The gro...
PubMed

A Study on the Application of Distributed System Technology-Guided Machine Learning in Malware Detection

Comput Intell Neurosci
Wiley, 2022DOI: 10.1155/2022/4977898https://creativecommons.org/licenses/by/4.0/
In recent years, with the development of information technology, the Internet has become an essential tool for human daily life. However, as the popularity and scale of the Internet continue to expand, malware has also emerged as an increasingly wide...
PubMed

The rise of obfuscated Android malware and impacts on detection methods

PeerJ Comput Sci
PeerJ, Inc, 2022DOI: 10.7717/peerj-cs.907https://creativecommons.org/licenses/by/4.0/
The various application markets are facing an exponential growth of Android malware. Every day, thousands of new Android malware applications emerge. Android malware hackers adopt reverse engineering and repackage benign applications with their malic...
PubMed

Digital Forensics for Malware Classification: An Approach for Binary Code to Pixel Vector Transition

Comput Intell Neurosci
Wiley, 2022DOI: 10.1155/2022/6294058https://creativecommons.org/licenses/by/4.0/
The most often reported danger to computer security is malware. Antivirus company AV-Test Institute reports that more than 5 million malware samples are created each day. A malware classification method is frequently required to prioritize these occu...
PubMed

CSMC: A Secure and Efficient Visualized Malware Classification Method Inspired by Compressed Sensing

Sensors (Basel)
Multidisciplinary Digital Publishing Institute (MDPI), 2024DOI: 10.3390/s24134253https://creativecommons.org/licenses/by/4.0/
With the rapid development of the Internet of Things (IoT), the sophistication and intelligence of sensors are continually evolving, playing increasingly important roles in smart homes, industrial automation, and remote healthcare. However, these int...
PubMed

CyberSentinel: A Transparent Defense Framework for Malware Detection in High-Stakes Operational Environments

Sensors (Basel)
Multidisciplinary Digital Publishing Institute (MDPI), 2024DOI: 10.3390/s24113406https://creativecommons.org/licenses/by/4.0/
Malware classification is a crucial step in defending against potential malware attacks. Despite the significance of a robust malware classifier, existing approaches reveal notable limitations in achieving high performance in malware classification. ...
PubMed

Detecting Malware with Information Complexity

Entropy (Basel)
Multidisciplinary Digital Publishing Institute (MDPI), 2020DOI: 10.3390/e22050575http://creativecommons.org/licenses/by/4.0/
Malware concealment is the predominant strategy for malware propagation. Black hats create variants of malware based on polymorphism and metamorphism. Malware variants, by definition, share some information. Although the concealment strategy alters t...
PubMed

An Efficient DenseNet-Based Deep Learning Model for Malware Detection

Entropy (Basel)
Multidisciplinary Digital Publishing Institute (MDPI), 2021DOI: 10.3390/e23030344https://creativecommons.org/licenses/by/4.0/
Recently, there has been a huge rise in malware growth, which creates a significant security threat to organizations and individuals. Despite the incessant efforts of cybersecurity research to defend against malware threats, malware developers discov...
PubMed

Efficient Windows malware identification and classification scheme for plant protection information systems

Front Plant Sci
Frontiers Media SA, 2023DOI: 10.3389/fpls.2023.1123696https://creativecommons.org/licenses/by/4.0/
Due to developments in science and technology, the field of plant protection and the information industry have become increasingly integrated, which has resulted in the creation of plant protection information systems. Plant protection information sy...
PubMed

AndroMalPack: enhancing the ML-based malware classification by detection and removal of repacked apps for Android systems

Sci Rep
Nature Publishing Group, 2022DOI: 10.1038/s41598-022-23766-whttps://creativecommons.org/licenses/by/4.0/
Due to the widespread usage of Android smartphones in the present era, Android malware has become a grave security concern. The research community relies on publicly available datasets to keep pace with evolving malware. However, a plethora of apps i...
PubMed

Deep learning based Sequential model for malware analysis using Windows exe API Calls

PeerJ Comput Sci
PeerJ, Inc, 2020DOI: 10.7717/peerj-cs.285https://creativecommons.org/licenses/by/4.0/
Malware development has seen diversity in terms of architecture and features. This advancement in the competencies of malware poses a severe threat and opens new research dimensions in malware detection. This study is focused on metamorphic malware, ...
PubMed

AndroDex: Android Dex Images of Obfuscated Malware

Sci Data
Nature Publishing Group, 2024DOI: 10.1038/s41597-024-03027-3https://creativecommons.org/licenses/by/4.0/
With the emergence of technology and the usage of a large number of smart devices, cyber threats are increasing. Therefore, research studies have shifted their attention to detecting Android malware in recent years. As a result, a reliable and large-...
PubMed

An Attribute Extraction for Automated Malware Attack Classification and Detection Using Soft Computing Techniques

Comput Intell Neurosci
Wiley, 2022DOI: 10.1155/2022/5061059https://creativecommons.org/licenses/by/4.0/
Malware has grown in popularity as a method of conducting cyber assaults in former decades as a result of numerous new deception methods employed by malware. To preserve networks, information, and intelligence, malware must be detected as soon as fea...
PubMed

IoT malware: An attribute-based taxonomy, detection mechanisms and challenges

Peer Peer Netw Appl
2023DOI: 10.1007/s12083-023-01478-w© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
During the past decade, the Internet of Things (IoT) has paved the way for the ongoing digitization of society in unique ways. Its penetration into enterprise and day-to-day lives improved the supply chain in numerous ways. Unfortunately, the profuse...
PubMed

Intelligent malware detection based on graph convolutional network

J Supercomput
2021DOI: 10.1007/s11227-021-04020-y© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Malware has seriously threatened the safety of computer systems for a long time. Due to the rapid development of anti-detection technology, traditional detection methods based on static analysis and dynamic analysis have limited effects. With its bet...
PubMed

Deep Feature Extraction and Classification of Android Malware Images

Sensors (Basel)
Multidisciplinary Digital Publishing Institute (MDPI), 2020DOI: 10.3390/s20247013http://creativecommons.org/licenses/by/4.0/
The Android operating system has gained popularity and evolved rapidly since the previous decade. Traditional approaches such as static and dynamic malware identification techniques require a lot of human intervention and resources to design the malw...