Modeling Trust Based Risk Management in Cloud Adoption using Fuzzy Inference System

Modeling Trust Based Risk Management in Cloud Adoption using Fuzzy Inference System

Shikha Gupta (Ansal University, Haryana, India) and Anil K. Saini (Guru Gobind Singh Indraprastha University, School of Management Studies, India)
Copyright: © 2017 |Pages: 9
DOI: 10.4018/IJTD.2017010104
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Cloud has revolutionized the entire landscape of IT usage, storage and maintenance. It has shifted the focus from owning physical IT infrastructure, facility and storage to the use of same in an abstract form with pay per use facility. This has led to economizing the entire IT infrastructure. Cloud's various characteristics including on demand pay per use, scalability and flexibility of computing highly depends on cloud service provider which can often lead to low results and serious issues. These issues may include concerns about losses due to non-compliance with the promises made. Hence selection of cloud service provider can play a positive or negative role in establishing an initial trust between the cloud service client and provider. The authors propose a model of Trust based Risk management of cloud adoption which can be used by cloud users. The model provides the functioning of comparing service providers using calculated trust ratings.
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Cloud Computing can be defined as a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction (Mell & Grance, 2011). The various characteristics of cloud computing including on demand, pay per use, flexibility, scalability and others have changed the entire IT infrastructure and computing from physical to virtual and abstract usage, storage and maintenance (Tripathi & Mishra, 2011). The cloud is offered in various service models which are Infrastructure as a Service (Iaas), Platform as a Service (Paas), Software as a Service (Saas) and the deployment models: private, community, and public and hybrid cloud (Gupta et al, 2016). Cloud computing has changed from self-owned IT infrastructure and computing to rented and on demand computing as a utility like other utilities e.g. electricity. Since this approach involves dependence on other party called cloud services provider who renders services in terms of usage maintenance and storage and others on demand so dependability on the provider for all the service is a crucial point and hence the selection of appropriate provider and knowledge of various points to be considered while selecting an appropriate provider can solve maximum problem at customers’ end.

This paper proposes a trust based risk management model based on Fuzzy Inference System approach comprising of Mamdani Fuzzy inference approach and Tageaky Sugeno fuzzy-inference approach to develop trust based risk management. The model uses trust framework developed by Cloud Service Management Index Consortium (SMIC) for Key Performance Indicators (KPIs) for cloud service selection (CSMIC, 2011).

The model for managing risk of cloud adoption works on developing initial trust on cloud service providers through selection of cloud service providers on key performance indicators.

The model is based on the framework of cloud adoption developed by Gupta et al. (2016). The framework considers trust as one of the major factors of cloud adoption which can be beneficial in managing risk of adopting cloud (Figure 1).

Figure 1.

Cloud adoption framework based on Gupta et al. (2016)


Managing Risk through Initial Trust Procedure

Trust can be defined as “the willingness of a party to be vulnerable to the action of another party based on the expectation that the other will perform a particular action important to the truster, irrespective to the ability to monitor or control that other party” (CSMCI, 2011). Cloud being an unknown technology adopted by companies generally in non-IT sector, migrating with initial trust is very crucial. As any company which plans to adopt cloud, lack of trust can hamper the adoption process (Iyer & Henderson, 2010). This is very crucial especially when client is planning to migrate his mission critical data and process (Mayer et al., 1995). So initial trust can help in “trust but verify” advice to companies opting for cloud adoption (Rashidi & Movahhedinia, 2012). Even the contractual agreement called service level agreement (SLA) has to be very exhaustive and should cover each and every detail (Rashidi & Movahhedinia, 2012; Aljazzaf, 2010; Huang & Nicol, 2013).

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