Enhancing Data Security in the User Layer of Mobile Cloud Computing Environment: A Novel Approach

Authors: Noah Oghenfego Ogwara, Krassie Petrova, Mee Loong, Yang, Stephen G. MacDonell
Published: 2020-12-15

Source: https://arxiv.org/abs/2012.08042

PDF: https://arxiv.org/pdf/2012.08042

AIにより推定されたラベル

侵入検知システム クラウドコンピューティング 機械学習の役割

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Abstract

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.