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Detection of Worms Over Cloud Environment: A Literature Survey

Detection of Worms Over Cloud Environment: A Literature Survey

Thangavel M., Jeyapriya B., Suriya K. S.
Copyright: © 2021 |Pages: 24
ISBN13: 9781799853398|ISBN10: 179985339X|EISBN13: 9781799853404
DOI: 10.4018/978-1-7998-5339-8.ch119
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MLA

M., Thangavel, et al. "Detection of Worms Over Cloud Environment: A Literature Survey." Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing, edited by Information Resources Management Association, IGI Global, 2021, pp. 2472-2495. https://doi.org/10.4018/978-1-7998-5339-8.ch119

APA

M., T., B., J., & S., S. K. (2021). Detection of Worms Over Cloud Environment: A Literature Survey. In I. Management Association (Ed.), Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing (pp. 2472-2495). IGI Global. https://doi.org/10.4018/978-1-7998-5339-8.ch119

Chicago

M., Thangavel, Jeyapriya B., and Suriya K. S. "Detection of Worms Over Cloud Environment: A Literature Survey." In Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing, edited by Information Resources Management Association, 2472-2495. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-5339-8.ch119

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Abstract

In recent years, computer worms are the remarkable difficulties found in the distributed computing. The location of worms turns out to be more unpredictable since they are changing quickly and much more refined. The difficulties in gathering worm's payload were recognized for identifying and gathering worm's payloads and the honey pot which is high-intelligent to gather the payload of zero-day polymorphic heterogeneous and homogeneous stages in distributed computing. The Signature-based discovery of worms strategies work with a low false-positive rate. We propose an irregularity based interruption location instrument for the cloud which specifically benefits from the virtualization advancements all in all. Our proposed abnormality location framework is detached from spreading computer worm contamination and it can recognize new computer worms. Utilizing our methodology, a spreading computer worm can be distinguished on the spreading conduct itself without getting to or straightforwardly affecting running virtual machines of the cloud.

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