Results 51 to 60 of about 37,609 (225)
Intelligent Vision-Based Malware Detection and Classification Using Deep Random Forest Paradigm
IEEE Access, 2020 Malware is a rapidly increasing menace to modern computing. Malware authors continually incorporate various sophisticated features like code obfuscations to create malware variants and elude detection by existing malware detection systems.
S. Abijah Roseline +3 more
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Impact Analysis of Malware Based on Call Network API with Heuristic Detection Method [PDF]
, 2020 Malware is a program that has a negative influence on computer systems that don't have user permissions. The purpose of making malware by hackers is to get profits in an illegal way. Therefore, we need a malware analysis.
Suryati, One Tika +3 more
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IEEE AccessCloud computing is integral to modern IT infrastructure, with Linux-based virtual machines (VMs) comprising 95% of public cloud environments. This widespread use makes Linux VMs a prime target for cyberattacks, particularly advanced malware designed for ...
Tom Landman, Nir Nissim
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Reverse Engineering untuk Analisis Malware Remote Access Trojan
JEPIN (Jurnal Edukasi dan Penelitian Informatika), 2019 Para hacker menggunakan malware Remote Access Trojan untuk merusak sistem kemudian mencuri data para korbannya. Diperlukan analisis mendalam mengenai malware baru-baru ini karena malware dapat berkamuflase seperti sistem tidak dicurigai.
Tesa Pajar Setia +2 more
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FAM: Featuring Android Malware for Deep Learning-Based Familial Analysis
IEEE Access, 2022 To handle relentlessly emerging Android malware, deep learning has been widely adopted in the research community. Prior work proposed deep learning-based approaches that use different features of malware, and reported a high accuracy in malware detection,
Younghoon Ban +4 more
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Evaluation of Supervised Machine Learning Techniques for Dynamic Malware Detection
International Journal of Computational Intelligence Systems, 2018 Nowadays, security of the computer systems has become a major concern of security experts. In spite of many antivirus and malware detection systems, the number of malware incidents are increasing day by day.
Hongwei Zhao +3 more
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Mal-Detect: An intelligent visualization approach for malware detection
Journal of King Saud University: Computer and Information Sciences, 2022 Recent outbreaks of pandemics have deepened the adoption and use of IT-based systems. This development has led to an exponential increase in cyberattacks caused by malware.
Olorunjube James Falana +3 more
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Journal of Computer Virology and Hacking Techniques, 2020 When training a machine learning model, there is likely to be a tradeoff between accuracy and the diversity of the dataset. Previous research has shown that if we train a model to detect one specific malware family, we generally obtain stronger results as compared to a case where we train a single model on multiple diverse families. However, during the
Samanvitha Basole +2 more
openaire +5 more sources
Morphological detection of malware [PDF]
2008 3rd International Conference on Malicious and Unwanted Software (MALWARE), 2008 In the field of malware detection, method based on syntactical consideration are usually efficient. However, they are strongly vulnerable to obfuscation techniques. This study proposes an efficient construction of a morphological malware detector based on a syntactic and a semantic analysis, technically on control flow graphs of programs (CFG).
Bonfante, Guillaume +2 more
openaire +3 more sources
Applied Sciences, 2020 Malware detection and classification methods are being actively developed to protect personal information from hackers. Global images of malware (in a program that includes personal information) can be utilized to detect or classify it.
Sejun Jang, Shuyu Li, Yunsick Sung
doaj +1 more source