DTRM: A new reputation mechanism to enhance data trustworthiness for high-performance cloud computing

• Published in: Future generation computer systems 2018-06, Vol.83, p.293-302
• Main Authors: Lin, Hui, Hu, Jia, Xu, Chuanfeng, Ma, Jianfeng, Yu, Mengyang
• Format: Article
• Language: English
• Subjects: Cloud computing; Data veracity; Reputation mechanism; Trustworthiness
• ISSN: 0167-739X; 1872-7115
• DOI: 10.1016/j.future.2018.01.026

Cloud computing and the mobile Internet have been the two most influential information technology revolutions, which intersect in mobile cloud computing (MCC). The burgeoning MCC enables the large-scale collection and processing of big data, which demand trusted, authentic, and accurate data to ensure an important but often overlooked aspect of big data — data veracity. Troublesome internal attacks launched by internal malicious users is one key problem that reduces data veracity and remains difficult to handle. To enhance data veracity and thus improve the performance of big data computing in MCC, this paper proposes a Data Trustworthiness enhanced Reputation Mechanism (DTRM) which can be used to defend against internal attacks. In the DTRM, the sensitivity-level based data category, Metagraph theory based user group division, and reputation transferring methods are integrated into the reputation query and evaluation process. The extensive simulation results based on real datasets show that the DTRM outperforms existing classic reputation mechanisms under bad mouthing attacks and mobile attacks. •A Data Trustworthiness enhanced Reputation Mechanism (DTRM) was proposed.•The DTRM outperforms existing algorithms under bad mouthing and mobile attacks.•The DTRM integrates the Metagraph theory based and reputation transferring methods.