  This paper reviews existing Intrusion Detection Systems (IDS) that target the
Mobile Cloud Computing (MCC), Cloud Computing (CC), and Mobile Device (MD)
environment. The review identifies the drawbacks in existing solutions and
proposes a novel approach towards enhancing the security of the User Layer (UL)
in the MCC environment. The approach named MINDPRES (Mobile- Cloud Intrusion
Detection and Prevention System) combines a host-based IDS and network-based
IDS using Machine Learning (ML) techniques. It applies dynamic analysis of both
device resources and network traffic in order to detect malicious activities at
the UL in the MCC environment. Preliminary investigations show that our
approach will enhance the security of the UL in the MCC environment. Our future
work will include the development and the evaluation of the proposed model
across the various mobile platforms in the MCC environment.
