Didroid: Android malware classification and characterization using deep image learning

A Rahali, AH Lashkari, G Kaur, L Taheri… - Proceedings of the …, 2020 - dl.acm.org
The unrivaled threat of android malware is the root cause of various security problems on
the internet. Although there are remarkable efforts in detection and classification of android …

Explaining ai for malware detection: Analysis of mechanisms of malconv

S Bose, T Barao, X Liu - 2020 international joint conference on …, 2020 - ieeexplore.ieee.org
In recent years, machine learning has been used in a very wide variety of applications and
malware detection is no exception. Because of its fast and widespread adaptation to various …

An optimized KNN model for signature-based malware detection

TA Assegie - Tsehay Admassu Assegie." An Optimized KNN Model …, 2021 - papers.ssrn.com
Malware is a computer program developed with the intent of disrupting, stealing, and
compromising a computer system. In recent advances in technology and internet use …

[HTML][HTML] IMCMK-CNN: A lightweight convolutional neural network with Multi-scale Kernels for Image-based Malware Classification

D Zhang, Y Song, Q **ang, Y Wang - Alexandria Engineering Journal, 2025 - Elsevier
Rapid and accurate identification of unknown malware and its variants is the premise and
basis for the effective prevention of malicious attacks. However, with the explosive growth of …

Improving classification performance for malware detection using genetic programming feature selection techniques

H Harahsheh, M Alshraideh, S Al-Sharaeh… - Journal of Applied …, 2023 - Taylor & Francis
Malware is the term used to describe any malicious software or code that is harmful to
systems. From day to day, new malicious programs appear. To classify malware according …

Experience Report: Using JA4+ Fingerprints for Malware Detection in Encrypted Traffic

P Matoušek, O Ryšavý… - 2024 20th International …, 2024 - ieeexplore.ieee.org
Detection of malware communications is limited due to encryption. Malware control,
updates, and distribution are encapsulated in TLS tunnels, making it difficult to distinguish …

[BOOK][B] Towards explainability in machine learning for Malware detection

S Bose - 2020 - search.proquest.com
Malware has crippled computer systems, caused financial losses on the order of billions of
dollars and denied access to services for millions of users worldwide. Detecting malware …

Detection technology of malicious code family based on BiLSTM-CNN

G Wang, T Lu, H Yin - Journal of Physics: Conference Series, 2020 - iopscience.iop.org
The explosive growth of the number of malicious code makes it one of the important threats
to network security. Among them, a new type of malicious code family accounts for a small …

[BOOK][B] Application Whitelisting as a Malicious Code Protection Control

GR Galloway - 2020 - search.proquest.com
Malicious code protection is often seen as synonymous with antivirus. Antivirus is a form of a
negative security control. Much of the current and historical research into malicious code …

NBP-MS: Malware Signature Generation Based on Network Behavior Profiling

Z Shi, X Wang, P Liu - 2022 26th International Conference on …, 2022 - ieeexplore.ieee.org
With the proliferation of malware, the detection and classification of malware have been hot
topics in the academic and industrial circles of cyber security, and the generation of malware …