• home
• current students
• graduate
• events

Presenter: Abdulaziz Aldribi
Supervisor:

Date: Thu, August 9, 2018
Time: 11:00:00 - 12:00:00
Place: ECS 660

ABSTRACT

Summary 

The adoption of cloud computing has increased dramatically in recent years due to attractive features such as flexibility, cost reductions, scalability, and pay per use. However, the security of cloud environments remain a crucial concern for existing and potential cloud customers. Cloud computing is faced with a multidimensional and rapidly evolving threat landscape, which makes intrusion detection more challenging. In this seminar, a new hypervisor-based cloud intrusion detection system (IDS) that uses online multivariate statistical change analysis to detect anomalous network behaviors will be introduced. As a departure from the conventional monolithic network IDS feature model, we leverage the fact that a hypervisor consists of a collection of instances, to introduce an instance-oriented feature model that exploits individual as well as correlated behaviors of instances to improve the detection capability. The proposed approach is evaluated by collecting and using a new cloud intrusion dataset that includes a wide variety of attack vectors.