Detection of enumeration attacks in cloud environments using infrastructure log data

Most computer services nowadays are provided in cloud environments. Inevitably, every individual needs to use these environments when they have to use computer services. Considering cyber threats in the cloud infrastructure, security and privacy conservation of one is really challenging. Out of date techniques are no more executable in these infrastructures. However, machine learning algorithms due to capable of handling massive data, are effective on this theme. In this project, we proposed machine learning algorithms to detect threats in the cloud environment. A basic user-friendly dashboard is developed for security analysts to conveniently monitor detected threats by this system. eSentire could benefit from this project by protecting its own customers owing to having state-of-the-art security solutions.

Faculty Supervisor:

Ali Dehghantanha


Samira Eisaloo Gharghasheh


eSentire Inc.


Computer science


Information and cultural industries


University of Guelph



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