Malware visualization - Open Access .click

Computers & Security, 2022
With the ever-increasing threat of malware attacks, building an effective malware classifier to detect malware promptly is of utmost importance. Malware visualization approaches and deep learning techniques have proven effective in classifying sophisticated malware from benchmark datasets.
Conti M., Khandhar S., Vinod P.
openaire +6 more sources

Visual attention for malware classification

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications IV, 2022
Amidst the extensive global integration of computer systems and augmented connectivity, there have been numerous difficulties within ensuring confidentiality, integrity and availability across all systems. Malware is an ever-present and persistent challenge for security systems of all sorts.
Alsadi N +5 more
openaire +2 more sources

Malware visualization and detection using DenseNets

Personal and Ubiquitous Computing, 2021
Rapid advancement in the sophistication of malware has posed a serious impact on the device connected over the Internet. Malware writing is driven by economic benefits; thus, an alarming increase in malware variants is witnessed. Recently, a large volume of malware attacks are reported on Internet of Things (IoT) networks; as these devices are exposed ...
V. Anandhi, P. Vinod, Varun G. Menon
openaire +1 more source

Image visualization based malware detection

2013 IEEE Symposium on Computational Intelligence in Cyber Security (CICS), 2013
Malware detection is one of the challenging tasks in Cyber security. The advent of code obfuscation, metamorphic malware, packers and zero day attacks has made malware detection a challenging task. In this paper we present a visualization based approach for malware detection.
Kesav Kancherla, Srinivas Mukkamala
openaire +1 more source

malware classification
deep learning
malware

machine learning
malware detection
malware analysis

computer security
cybersecurity
cyber security