A survey of recent advances in deep learning models for detecting malware in desktop and mobile platforms
Malware is one of the most common and severe cyber threats today. Malware infects
millions of devices and can perform several malicious activities including compromising …
millions of devices and can perform several malicious activities including compromising …
[HTML][HTML] Android Malware Detection and Identification Frameworks by Leveraging the Machine and Deep Learning Techniques: A Comprehensive Review
The ever-increasing growth of online services and smart connectivity of devices have posed
the threat of malware to computer system, android-based smart phones, Internet of Things …
the threat of malware to computer system, android-based smart phones, Internet of Things …
SDIF-CNN: Stacking deep image features using fine-tuned convolution neural network models for real-world malware detection and classification
S Kumar, K Panda - Applied Soft Computing, 2023 - Elsevier
The detection of malware is a complex problem in the area of Internet security. Developing a
malware defense system that is less costly to detect large-scale malware is needed. This …
malware defense system that is less costly to detect large-scale malware is needed. This …
A Viewpoint Adaptation Ensemble Contrastive Learning framework for vessel type recognition with limited data
Abstract Unmanned Aerial Vehicle (UAV)-based systems are gaining increasing attention in
the maritime industry, but one of their major challenges is accurately identifying vessel types …
the maritime industry, but one of their major challenges is accurately identifying vessel types …
MIGAN: GAN for facilitating malware image synthesis with improved malware classification on novel dataset
O Sharma, A Sharma, A Kalia - Expert Systems with Applications, 2024 - Elsevier
Malware visualization is a technique wherein malware binaries are represented as
grayscale or color images in order to identify and extract discriminating features for …
grayscale or color images in order to identify and extract discriminating features for …
Efficient android malware identification with limited training data utilizing multiple convolution neural network techniques
A Ksibi, M Zakariah, L Almuqren… - Engineering Applications of …, 2024 - Elsevier
Abstract The Internet of Things (IoT) has experienced phenomenal expansion over the past
few years and has emerged as one of the most dynamic sectors of the international market …
few years and has emerged as one of the most dynamic sectors of the international market …
Application of transfer learning approach for diabetic retinopathy classification
Diabetes is a disorder of the metabolism caused by high glucose levels in the body.
Diabetes causes eye deficiency, also known as Diabetic Retinopathy (DR), which causes …
Diabetes causes eye deficiency, also known as Diabetic Retinopathy (DR), which causes …
A holistic approach to ransomware classification: Leveraging static and dynamic analysis with visualization
B Yamany, MS Elsayed, AD Jurcut, N Abdelbaki… - Information, 2024 - mdpi.com
Ransomware is a type of malicious software that encrypts a victim's files and demands
payment in exchange for the decryption key. It is a rapidly growing and evolving threat that …
payment in exchange for the decryption key. It is a rapidly growing and evolving threat that …
[HTML][HTML] Optimizing brain tumor classification with hybrid CNN architecture: Balancing accuracy and efficiency through oneAPI optimization
A brain tumour is a malignant condition that spreads extremely quickly and requires rapid
detection. In recent years, it has become apparent that deep learning is a promising …
detection. In recent years, it has become apparent that deep learning is a promising …
Novel hybrid classifier based on fuzzy type-III decision maker and ensemble deep learning model and improved chaos game optimization
This paper presents a unique hybrid classifier that combines deep neural networks with a
type-III fuzzy system for decision-making. The ensemble incorporates ResNet-18, Efficient …
type-III fuzzy system for decision-making. The ensemble incorporates ResNet-18, Efficient …