A Context Aware Reputation Mechanism for Enhancing Big Data Veracity in Mobile Cloud Computing

Data veracity ensures that the data used are trusted, authentic and protected from unauthorized access and modification. In order to implement the veracity of big data, specific trust models and approaches must be designed and developed. In this paper, a category based context aware and recommendation incentive based reputation mechanism (CCRM) is proposed to defend against the internal attacks to enhance the big data veracity in mobile cloud computing (MCC). Simulation results and performance analysis demonstrate the superior performance of the CCRM in terms of the utility of the recommender, the reputation decrease speed and update accuracy, compared to the existing reputation mechanisms under internal collusion attacks and bad mouthing attacks in MCC.

[1]  Vasil Hnatyshin,et al.  The Practical OPNET User Guide for Computer Network Simulation , 2012 .

[2]  Sven G. Bilen,et al.  Increasing the veracity of event detection on social media networks through user trust modeling , 2014, 2014 IEEE International Conference on Big Data (Big Data).

[3]  Hui Lin,et al.  PA-SHWMP: a privacy-aware secure hybrid wireless mesh protocol for IEEE 802.11s wireless mesh networks , 2012, EURASIP J. Wirel. Commun. Netw..

[4]  ParkSang Oh,et al.  Trust management on user behavioral patterns for a mobile cloud computing , 2013 .

[5]  Samee Ullah Khan,et al.  Future Generation Computer Systems ( ) – Future Generation Computer Systems towards Secure Mobile Cloud Computing: a Survey , 2022 .

[6]  Okyay Kaynak,et al.  Big Data for Modern Industry: Challenges and Trends [Point of View] , 2015, Proc. IEEE.

[7]  Elisa Bertino Data Security - Challenges and Research Opportunities , 2013, Secure Data Management.

[8]  Andrea J. Goldsmith,et al.  Variable-rate variable-power MQAM for fading channels , 1997, IEEE Trans. Commun..

[9]  Xuemin Shen,et al.  Exploiting mobile crowdsourcing for pervasive cloud services: challenges and solutions , 2015, IEEE Communications Magazine.

[10]  Yong Zhang,et al.  A Novel Reputation Computation Model Based on Subjective Logic for Mobile Ad Hoc Networks , 2009, 2009 Third International Conference on Network and System Security.

[11]  Ahmed Hammam,et al.  A trust management system for ad-hoc mobile clouds , 2013, 2013 8th International Conference on Computer Engineering & Systems (ICCES).

[12]  Li Xu,et al.  A reliable recommendation and privacy-preserving based cross-layer reputation mechanism for mobile cloud computing , 2015, Future Gener. Comput. Syst..

[13]  Wei Cheng,et al.  ARTSense: Anonymous reputation and trust in participatory sensing , 2013, 2013 Proceedings IEEE INFOCOM.

[14]  Robert K. Cunningham,et al.  Computing on masked data: a high performance method for improving big data veracity , 2014, 2014 IEEE High Performance Extreme Computing Conference (HPEC).

[15]  Mucheol Kim,et al.  Trust management on user behavioral patterns for a mobile cloud computing , 2013, Cluster Computing.

[16]  Haiying Shen,et al.  An Efficient and Trustworthy Resource Sharing Platform for Collaborative Cloud Computing , 2014, IEEE Transactions on Parallel and Distributed Systems.

[17]  Zhu Han,et al.  Truthful Mechanisms for Secure Communication in Wireless Cooperative System , 2013, IEEE Transactions on Wireless Communications.

[18]  Günther Pernul,et al.  Trust and Big Data: A Roadmap for Research , 2014, 2014 25th International Workshop on Database and Expert Systems Applications.