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dc.contributor.authorOgwara, NOen_NZ
dc.contributor.authorPetrova, Ken_NZ
dc.contributor.authorYang, MLBen_NZ
dc.contributor.authorMacDonell, SGen_NZ
dc.date.accessioned2021-08-10T00:47:02Z
dc.date.available2021-08-10T00:47:02Z
dc.date.copyright2020en_NZ
dc.identifier.citationarXiv:2012.08042
dc.identifier.urihttp://hdl.handle.net/10292/14413
dc.description.abstractThis 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.
dc.publisherarXiv
dc.relation.urihttps://arxiv.org/abs/2012.08042
dc.rightsAs a repository for scholarly material, arXiv keeps a permanent record of every article and version posted. All articles on arXiv.org can be viewed and downloaded freely by anyone.
dc.subjectMobile Cloud Computing; Data Security; Intrusion Detection System; User Layer; MINDPRES
dc.titleEnhancing Data Security in the User Layer of Mobile Cloud Computing Environment: A Novel Approachen_NZ
dc.typeConference Contribution
dc.rights.accessrightsOpenAccessen_NZ
aut.relation.volumeabs/2012.08042en_NZ
pubs.elements-id397240


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