A context aware reputation mechanism for enhancing big data veracity in mobile cloud computing

Data veracity ensures that the data used are trabusted, authentic and protected from unauthorized access and modification. It is under greater focus than ever before in big data research as data are used for critical decision makings more often. 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). In CCRM, the data category and context sensing technologies, security relevance evaluation model and Vickrey-Clark-Groves (VCG) based recommendation incentive scheme are integrated into the reputation evaluation process to defend against the insider attacks to enhance the data veracity. 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.