Malware analysis and detection using machine learning algorithms

MS Akhtar, T Feng - Symmetry, 2022 - mdpi.com
One of the most significant issues facing internet users nowadays is malware. Polymorphic
malware is a new type of malicious software that is more adaptable than previous …

Fusion models for cyber threat defense: integrating clustering with kmeans, random forests, and SVM against windows malware

A Ramezani - 2024 IEEE World AI IoT Congress (AIIoT), 2024 - ieeexplore.ieee.org
Innovative defensive techniques are needed to address threats caused by Windows
malware that are becoming more prevalent. This study presents a novel method for …

Deep learning based residual attention network for malware detection in CyberSecurity

R Sharma, S Deshmukh, A Mannava… - 2022 6th International …, 2022 - ieeexplore.ieee.org
As the threat for viruses and malware is increasing so detecting them accurately is very
important. By studying and researching different papers, it is finally known that the main …

Evolutionary computation and machine learning in security

S Picek, D Jakobovic - Proceedings of the Genetic and Evolutionary …, 2022 - dl.acm.org
Stjepan Picek received his PhD in 2015 as a double doctorate under the supervision of Lejla
Batina, Elena Marchiori (Radboud University Nijmegen, The Netherlands), and Domagoj …

Research on APT Malware Detection Based on BERT-Transformer-TextCNN Modeling

J Zhang, S Liu, Z Liu - Proceedings of the 2024 International Conference …, 2024 - dl.acm.org
In recent years, with the development of the Internet, APT malware detection remains an
important issue for society. The lengthy nature of API sequence text leads to polysemy …

Malware Detection Employing Deep Neural Networks

SG Nayak, S Kurup, J Andrew - 2024 10th International …, 2024 - ieeexplore.ieee.org
Malware, malicious software designed to disrupt, damage, or gain unauthorized access to
computer systems, poses a significant and evolving threat to cybersecurity. Malware …

[PDF][PDF] Machine Learning in Malware Analysis: Current Trends and Future Directions.

S Altaha, K Riad - … Journal of Advanced Computer Science & …, 2024 - saiconference.com
Malware analysis is a critical component of cybersecurity due to the increasing
sophistication and the widespread of malicious software. Machine learning is highly …

[PDF][PDF] Prediction of novel malware using hybrid convolution neural network and long short-term memory approach.

N Pachhala, S Jothilakshmi, BP Battula - International Journal of …, 2024 - academia.edu
The rapid evolution of network communication technologies has led to the emergence of
new forms of malware and cybercrimes, posing significant threats to user safety, network …

A Comparison Study to Detect Malware using Deep Learning and Machine learning Techniques

B Bokolo, R **ad, Q Liu - … on Big Data and Artificial Intelligence …, 2023 - ieeexplore.ieee.org
Malware creation has evolved from basic malware that is easy to detect to complicated
malware that is obfuscated and quickly adaptive, raising the challenge of being easily …

Malware Detection and Classification for URLs using Ensemble Learning

S Uke, G Gite, H Hirkani, I Bassan… - 2024 4th International …, 2024 - ieeexplore.ieee.org
The advent of the digital age has brought about previously unheard levels of connectedness
and information availability, as well as an increase in cyber threats. Unauthorized Uniform …