期刊
CMC-COMPUTERS MATERIALS & CONTINUA
卷 74, 期 2, 页码 2641-2659出版社
TECH SCIENCE PRESS
DOI: 10.32604/cmc.2023.028796
关键词
Intrusion prevention system; spamming; KNN classification; spam; cyber security; botnet
Cloud computing is an attractive and cost-saving model that offers online services to end-users, allowing them to access data from any node. However, cloud security is a major concern due to various malware attacks from internal and external sources. This paper proposes a tool that uses Cloudflare and K-nearest neighbors (KNN) classification to prevent spamming attacks on cloud servers. Cloudflare blocks attacker's IP addresses, while KNN classifiers identify the location of spammers. The article also discusses various prevention techniques, compares with other studies, and draws conclusions based on different results.
Cloud computing is one of the most attractive and cost-saving models, which provides online services to end-users. Cloud computing allows the user to access data directly from any node. But nowadays, cloud secu-rity is one of the biggest issues that arise. Different types of malware are wreaking havoc on the clouds. Attacks on the cloud server are happening from both internal and external sides. This paper has developed a tool to prevent the cloud server from spamming attacks. When an attacker attempts to use different spamming techniques on a cloud server, the attacker will be intercepted through two effective techniques: Cloudflare and K-nearest neighbors (KNN) classification. Cloudflare will block those IP addresses that the attacker will use and prevent spamming attacks. However, the KNN classifiers will determine which area the spammer belongs to. At the end of the article, various prevention techniques for securing cloud servers will be discussed, a comparison will be made with different papers, a conclusion will be drawn based on different results.
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