Journal
IEEE TRANSACTIONS ON SERVICES COMPUTING
Volume 11, Issue 1, Pages 184-201Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TSC.2016.2549019
Keywords
Cloud computing; trust; malicious service; game theory; services community; cloud federation; social network; bootstrapping
Funding
- Fonds de Recherche du Quebec - Nature et Technologie (FRQNT)
- Natural Sciences and Engineering Research Council of Canada (NSERC)
- Khalifa University of Science, Technology & Research (KUS-TAR)
- Associated Research Unit of the National Council for Scientific Research (CNRS-Lebanon)
- American University (LAU)
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The prominence of cloud computing led to unprecedented proliferation in the number of web services deployed in cloud data centers. In parallel, service communities have gained recently increasing interest due to their ability to facilitate discovery, composition, and resource scaling in large-scale services' markets. The problem is that traditional community formation models may work well when all services reside in a single cloud but cannot support a multi-cloud environment. Particularly, these models overlook having malicious services that misbehave to illegally maximize their benefits and that arises from grouping together services owned by different providers. Besides, they rely on a centralized architecture whereby a central entity regulates the community formation; which contradicts with the distributed nature of cloud-based services. In this paper, we propose a three-fold solution that includes: trust establishment framework that is resilient to collusion attacks that occur to mislead trust results; bootstrapping mechanism that capitalizes on the endorsement concept in online social networks to assign initial trust values; and trust-based hedonic coalitional game that enables services to distributively form trustworthy multi-cloud communities. Experiments conducted on a real-life dataset demonstrate that our model minimizes the number of malicious services compared to three state-of-the-art cloud federations and service communities models.
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