Exploring lightweight deep learning solution for malware detection in IoT constraint environment
The present era is facing the industrial revolution. Machine-to-Machine (M2M)
communication paradigm is becoming prevalent. Resultantly, the computational capabilities …
communication paradigm is becoming prevalent. Resultantly, the computational capabilities …
[HTML][HTML] A Systematic Literature Review of Multimodal Emotion Recognition
Purpose: This literature review aims to identify Multimodal Emotion Recognition (MER) in
depth and breadth by analysing the topics, trends, modalities, and other supporting sources …
depth and breadth by analysing the topics, trends, modalities, and other supporting sources …
Image-Based Malware Classification Using QR and Aztec Codes
A Khadilkar, M Stamp - arxiv preprint arxiv:2412.08514, 2024 - arxiv.org
In recent years, the use of image-based techniques for malware detection has gained
prominence, with numerous studies demonstrating the efficacy of deep learning approaches …
prominence, with numerous studies demonstrating the efficacy of deep learning approaches …
Devising Malware Characterstics using Transformers
With the increasing number of cybersecurity threats, it becomes more difficult for researchers
to skim through the security reports for malware analysis. There is a need to be able to …
to skim through the security reports for malware analysis. There is a need to be able to …
Why GloVe Shows Negative Effects in Malware Classification
B **, Z Hu, J Wang, M Wei, Y Zhao… - 2022 IEEE 6th …, 2022 - ieeexplore.ieee.org
The past decades witness the development of various Machine Learning (ML) models for
malware classification. Semantic representation is a crucial basis for these classifiers. This …
malware classification. Semantic representation is a crucial basis for these classifiers. This …