Vulnerability scanning with google cloud platform

Document Type

Conference Proceeding

Publication Date

12-1-2019

Abstract

Cloud is completely flipping the concept of business nowadays. Reducing capital and operational expenditure to a great extent already drew attention of big companies and industries. Not only startups but also large existing giant companies are shifting their data from local server to a public cloud and sometimes even taking the initiative to build a public cloud to host their sensitive data. A cloud can provide storage services, computing services and also infrastructure without any capital or operational expenses. From a single user to a multi-national million-dollar business can easily receive several types of services from a public cloud. There are numerous cloud providers in the market. Among the prominent ones, few names are mentioned here, such as Amazon AWS, Google Cloud Platform (GCP), and Microsoft Azure etc. GCP offers a wide array of services for many organizations and individuals around the world like other cloud providers. But the question is, all those data, confidential information, intellectual property of individual or industries safe enough? Information has become the most expensive commodity in modern days. A government can be shutdown, a transport system can be disabled, annoying spam calls, phishing emails, cyber bullying and more security threats are existing around us. Can we trust a public service provider? Hence our initiative aims at investigating that GCP is secure from inside attackers. Why we chose inside attackers? Well the idea is to check if GCP can detect and ignore an attack launched internally. In this case it should be secure enough to prevent from outsiders as well. The research investigation would involve Distributed Denial of Service (DDoS) attacks against a local virtual machine (VM) launched from GCP. There is a broad spectrum of VM's available in GCP compute engine service.

Publication Title

Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019

First Page Number

1441

Last Page Number

1447

DOI

10.1109/CSCI49370.2019.00269

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