IMCFN: Image-based malware classification using fine-tuned convolutional neural network architecture
The volume, type, and sophistication of malware is increasing. Deep convolutional neural
networks (CNNs) have lately proven their effectiveness in malware binary detection through …
networks (CNNs) have lately proven their effectiveness in malware binary detection through …
Image-Based malware classification using ensemble of CNN architectures (IMCEC)
Both researchers and malware authors have demonstrated that malware scanners are
unfortunately limited and are easily evaded by simple obfuscation techniques. This paper …
unfortunately limited and are easily evaded by simple obfuscation techniques. This paper …
Visualization and deep-learning-based malware variant detection using OpCode-level features
Malicious software (malware) is a major threat to the systems and networks' security.
Although anti-malware products are used to protect systems and networks against malware …
Although anti-malware products are used to protect systems and networks against malware …
An automated vision-based deep learning model for efficient detection of android malware attacks
Recently, cybersecurity experts and researchers have given special attention to developing
cost-effective deep learning (DL)-based algorithms for Android malware detection (AMD) …
cost-effective deep learning (DL)-based algorithms for Android malware detection (AMD) …
IOT malware detection using static and dynamic analysis techniques: A systematic literature review
Abstract The Internet of Things (IoT) is reshaping the world with its potential to support new
and evolving applications in areas, such as healthcare, automation, remote monitoring, and …
and evolving applications in areas, such as healthcare, automation, remote monitoring, and …
MTHAEL: Cross-architecture IoT malware detection based on neural network advanced ensemble learning
D Vasan, M Alazab, S Venkatraman… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The complexity, sophistication, and impact of malware evolve with industrial revolution and
technology advancements. This article discusses and proposes a robust cross-architecture …
technology advancements. This article discusses and proposes a robust cross-architecture …
An enhanced deep learning neural network for the detection and identification of android malware
Android-based mobile devices have attracted a large number of users because they are
easy to use and possess a wide range of capabilities. Because of its popularity, Android has …
easy to use and possess a wide range of capabilities. Because of its popularity, Android has …
Visualized malware multi-classification framework using fine-tuned CNN-based transfer learning models
There is a massive growth in malicious software (Malware) development, which causes
substantial security threats to individuals and organizations. Cybersecurity researchers …
substantial security threats to individuals and organizations. Cybersecurity researchers …
A new super resolution Faster R-CNN model based detection and classification of urine sediments
The diagnosis of urinary tract infections and kidney diseases using urine microscopy images
has gained significant attention of medical community in recent years. These images are …
has gained significant attention of medical community in recent years. These images are …
Malware detection using genetic cascaded support vector machine classifier in Internet of Things
SK Gupta, B Pattnaik, V Agrawal… - 2022 Second …, 2022 - ieeexplore.ieee.org
The Internet of Things (IoT) is a network of computing devices that can transmit and obtain
data across a network without human intervention. In the last couple of decades, software …
data across a network without human intervention. In the last couple of decades, software …