Effective one-class classifier model for memory dump malware detection

M Al-Qudah, Z Ashi, M Alnabhan… - Journal of Sensor and …, 2023 - mdpi.com
Malware complexity is rapidly increasing, causing catastrophic impacts on computer
systems. Memory dump malware is gaining increased attention due to its ability to expose …

[PDF][PDF] An Effective Memory Analysis for Malware Detection and Classification.

R Sihwail, K Omar, KAZ Arifin - Computers, Materials & Continua, 2021 - cdn.techscience.cn
The study of malware behaviors, over the last years, has received tremendous attention from
researchers for the purpose of reducing malware risks. Most of the investigating experiments …

Performance enhancement of SVM-based ML malware detection model using data preprocessing

P Singh, SK Borgohain, J Kumar - 2022 2nd International …, 2022 - ieeexplore.ieee.org
The exponential proliferation and speedy propa-gation of malware have been a major
concern for computer users. Recently, Machine Learning (ML) is exploited as a sus-tainable …

An Ensemble approach for advance malware memory analysis using Image classification techniques

LK Vashishtha, K Chatterjee, SS Rout - Journal of Information Security and …, 2023 - Elsevier
New types of malware have emerged due to the increased use of computer systems and
web services, which are unsafe and harder to identify. The latest reports show that a new …

Minimized feature overhead malware detection machine learning model employing MRMR‐based ranking

P Singh, SK Borgohain, LD Sharma… - Concurrency and …, 2022 - Wiley Online Library
To deal with the huge amount of data, minimizing the overhead will play a key role in speedy
and efficient malware detection. We propose a machine learning (ML) malware detection …

MalwD&C: A Quick and Accurate Machine Learning-Based Approach for Malware Detection and Categorization

A Buriro, AB Buriro, T Ahmad, S Buriro, S Ullah - Applied Sciences, 2023 - mdpi.com
Malware, short for malicious software, is any software program designed to cause harm to a
computer or computer network. Malware can take many forms, such as viruses, worms …

Catch them alive: A malware detection approach through memory forensics, manifold learning and computer vision

AS Bozkir, E Tahillioglu, M Aydos, I Kara - Computers & Security, 2021 - Elsevier
The everlasting increase in usage of information systems and online services have triggered
the birth of the new type of malware which are more dangerous and hard to detect. In …

Byte-level malware classification based on markov images and deep learning

B Yuan, J Wang, D Liu, W Guo, P Wu, X Bao - Computers & Security, 2020 - Elsevier
In recent years, malware attacks have become serious security threats and have caused
huge losses. Due to the rapid growth of malware variants, how to quickly and accurately …

Assessment of supervised machine learning algorithms using dynamic API calls for malware detection

J Singh, J Singh - International Journal of Computers and …, 2022 - Taylor & Francis
Detection of malware using traditional malware detection techniques is very hard. Machine
Learning (ML) algorithms provide a solution to detect the malware which is being developed …

Zero-day malware detection and effective malware analysis using Shapley ensemble boosting and bagging approach

R Kumar, G Subbiah - Sensors, 2022 - mdpi.com
Software products from all vendors have vulnerabilities that can cause a security concern.
Malware is used as a prime exploitation tool to exploit these vulnerabilities. Machine …