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A novel deep learning-based approach for malware detection
Malware detection approaches can be classified into two classes, including static analysis
and dynamic analysis. Conventional approaches of the two classes have their respective …
and dynamic analysis. Conventional approaches of the two classes have their respective …
An efficient densenet-based deep learning model for malware detection
Recently, there has been a huge rise in malware growth, which creates a significant security
threat to organizations and individuals. Despite the incessant efforts of cybersecurity …
threat to organizations and individuals. Despite the incessant efforts of cybersecurity …
A new malware classification framework based on deep learning algorithms
Recent technological developments in computer systems transfer human life from real to
virtual environments. Covid-19 disease has accelerated this process. Cyber criminals' …
virtual environments. Covid-19 disease has accelerated this process. Cyber criminals' …
[HTML][HTML] A novel machine learning approach for detecting first-time-appeared malware
Conventional malware detection approaches have the overhead of feature extraction, the
requirement of domain experts, and are time-consuming and resource-intensive. Learning …
requirement of domain experts, and are time-consuming and resource-intensive. Learning …
MCFT-CNN: Malware classification with fine-tune convolution neural networks using traditional and transfer learning in Internet of Things
S Kumar - Future Generation Computer Systems, 2021 - Elsevier
With ever-increasing, internet-connected devices provide an opportunity to fulfil the
attacker's malicious intention. They use malicious programs to compromise the devices and …
attacker's malicious intention. They use malicious programs to compromise the devices and …
Intelligent vision-based malware detection and classification using deep random forest paradigm
Malware is a rapidly increasing menace to modern computing. Malware authors continually
incorporate various sophisticated features like code obfuscations to create malware variants …
incorporate various sophisticated features like code obfuscations to create malware variants …
Improving malicious email detection through novel designated deep-learning architectures utilizing entire email
In today's email dependent world, cyber criminals often target organizations using a variety
of social engineering techniques and specially crafted malicious emails. When successful …
of social engineering techniques and specially crafted malicious emails. When successful …
Resnext+: Attention mechanisms based on resnext for malware detection and classification
Malware detection and classification are crucial for protecting digital devices and information
systems. Accurate identification of malware enables researchers and incident responders to …
systems. Accurate identification of malware enables researchers and incident responders to …
Malware‐SMELL: A zero‐shot learning strategy for detecting zero‐day vulnerabilities
One of the most relevant security problems is inferring whether a program has malicious
intent (malware software). Even though Antivirus is one of the most popular approaches for …
intent (malware software). Even though Antivirus is one of the most popular approaches for …
ConRec: malware classification using convolutional recurrence
Today, the extensive reliae on technology has exposed us to a constant threat of
sophisticated malware attacks. Various automated malware production techniques have …
sophisticated malware attacks. Various automated malware production techniques have …