Paper Title :Malware Detection in the Cloud by Integrating Multiple Methods

Author :Meet Laheru, Krunal Vaghela

Article Citation :Meet Laheru ,Krunal Vaghela , (2023 ) " Malware Detection in the Cloud by Integrating Multiple Methods " , International Journal of Advances in Computer Science and Cloud Computing (IJACSCC) , pp. 34-38, Volume-11,Issue-1

Abstract : Malicious codes are proliferating at an alarming rate. These days, malware is the preferred means of attack for criminals (attackers), as criminals launch attacks on computers. Malware assaults are usually carried out through the Internet via email, fraudulent websites, or downloaded packages. Numerous kinds of malicious codes exist, including worms, viruses, rootkits, trojan horses, crypto-locker malware, adware, etc. Despite the reality that there is no tested way to detect malicious code, adopting cloud environments might reveal to be a beneficial approach. Malicious code has advanced to a new generation that is more effective at finding vulnerabilities by implementing advanced obfuscation and packing tactics. As a result of these circumstances, it is practically hard to identify sophisticated malware by using more traditional detection methods.In this paper, we proposed, malware detection in the cloud environment by combining various approaches. We use ANN malware dataset for evaluation. By comparing the outcomes of tests 1 and 2, we found that the proposed model improved accuracy while reducing data loss, which suggesting it is superior to alternative approaches. Keywords - Cloud-Environment, VM, Malware, Malware Detection.

Type : Research paper

Published : Volume-11,Issue-1

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