Detecting fraudulent activity in a cloud using privacy-friendly data aggregates

More users and companies make use of cloud services every day. They all expect a perfect performance and any issue to remain transparent to them. This last statement is very challenging to perform. A user’s activities in our cloud can a ect the overall performance of our servers, having an impact on other resources. We can consider these kind of activities as fraudulent. They can be either illegal activities, such as launching a DDoS attack or just activities which are undesired by the cloud provider, such as Bitcoin mining, which uses substantial power, reduces the life of the hardware and can possibly slow down other user’s activities. This article discusses a method to detect such activities by using non-intrusive, privacy-friendly data: billing data. We use OpenStack as an example with data provided by Telemetry, the component in charge of measuring resource usage for billing purposes. Results will be shown proving the e ciency of this method and ways to improve it will be provided as well as its advantages and disadvantages.