Feedback based Trust Management for Cloud Environment

Machhi, Sandip; Jethava, Gordhan

doi:10.1145/2905055.2905330

Cited by 10 publications

(6 citation statements)

References 20 publications

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“…This section includes assessing the credibility of HR and comparing the proposed method in mean squared error (MSE), average response time, latency average, and degree of time criteria to other methods. The proposed method in this paper is compared to the proposed methods in Awan et al (2020), Machhi and Jethava (2016), Habib et al (2011), and Chen and Wang (2017). Awan et al (2020) introduced a new trust management process that uses trust parameters to distinguish malicious and vulnerable nodes.…”

Section: Resultsmentioning

confidence: 99%

“…PEPA excels at compositionality and parsimony, allowing it to model structures of layered architectures and complex behaviors effectively. Machhi and Jethava (2016) suggested a trust management system that would easily root out inaccurate feedback based on cloud user behavior, aging aspect, plurality feedback and exogenous process, and calculate the service provider's trustworthiness. Besides, for a cloud computing marketplace, Habib et al (2011) suggested a multi-faceted trust management system structure.…”

Section: Resultsmentioning

confidence: 99%

“…Due to the cloud's dynamic nature and the unpredictable number of cloud customers for operation, maintaining trust feedback is extremely hard. Finding the credibility of trust feedback is critical since uncredible trust feedback will lead to incorrect trust outcomes (Machhi and Jethava, 2016). To satisfy high-security demands in cloud computing environments, managing trust associations is a major challenge.…”

Section: Introductionmentioning

confidence: 99%

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A new trust management framework based on the experience of users in industrial cloud computing using multi-criteria decision making

Khoruzhy

Bulyga

Voronkova

et al. 2021

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PurposeNowadays, cloud platforms are used in many fields, including e-commerce, web applications, data storage, healthcare, gaming, mobile social networks, etc. However, security and privacy are still two significant concerns in this area. The target of this paper is to present a system for trust management in industrial cloud computing using the multi-criteria decision making (MCDM) approach. MCDM techniques have been developed to accommodate a wide range of applications. As a result, hundreds of approaches have been generated with even minor variations on current approaches spawning new study fields.Design/methodology/approachCloud computing provides a fully scalable, accessible and flexible computing platform for various applications. Due to the multiple applications that cloud computing has found in numerous life features, users and providers have considered providing security in cloud communications. Due to its distributive nature, dynamic space and lack of transparency in performing cloud computing, it faces many challenges in providing security. For security improvement, trust management can play a very influential role. This paper proposes a generic analytical methodology that uses a series of assessment criteria to evaluate current trust management testing prototypes in industrial cloud computing and related fields. The authors utilize a MCDM approach in the present article. Due to the multi-dimensionality of the sustainability objective and the complexities of socio-economic and biophysical processes, MCDM approaches have become progressively common in decision-making for sustainable energy.FindingsThe results of comparing and evaluating the performance of this model show its ability to manage trust and the ability to adapt to changes in the behavior of service providers quickly. Using a simulation, all results are confirmed. The results of simulations and evaluation of the present paper indicate that the proposed model provides a more accurate evaluation of the credibility of cloud service providers than other models.Practical implicationsThe number of cloud services and customers is vast and extremely competitive in cloud environments, where novel cloud services and customers can join at any time, while others can withdraw whenever they want. Because of cloud services' highly dynamic and dispersed design, trust management mechanisms must be highly flexible to obtain feedback and update trust outcomes as quickly as possible. The model presented in this article tries to improve users' trust in the cloud industry.Originality/valueUsing a method (MCDM) to find the best trust management solution based on user experience in industrial cloud computing is the novelty of this paper.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A new trust management framework based on the experience of users in industrial cloud computing using multi-criteria decision making

Khoruzhy

Bulyga

Voronkova

et al. 2021

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“…Unlike the SLA-focused measurements discussed earlier, SMI includes reputation metrics based on feedback from users, user experience and certification of compliance with industry best practice and regulations. In a similar vein, Machhi and Jethava (2016) present a trust management framework that measures service provider trustworthiness based on feedback, aging factor, and other parameters, while eliminating or otherwise discounting unreliable feedback. Indeed a number of works have sought to combine SLA metrics with feedback systems as a means of communicating trust in the service and vendor (see, for example, Nguyen et al 2010;Habib et al 2011;Yau and Yin 2011;Garg et al 2013;Noor, et al 2015;Tang et al 2017).…”

Section: Business Integritymentioning

confidence: 99%

Trustworthy Cloud Computing

Alofe

Fatema

2020

Palgrave Studies in Digital Business &Amp; Enabling Technologies

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Trustworthy cloud computing has been a central tenet of the European Union cloud strategy for nearly a decade. This chapter discusses the origins of trustworthy computing and specifically how the goals of trustworthy computing—security and privacy, reliability, and business integrity—are represented in computer science research. We call for further inter- and multi-disciplinary research on trustworthy cloud computing that reflect a more holistic view of trust.

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“…Feedback (or reputation) scores are then calculated by subtracting the total negative ratings from the total positive ones for each user. However, because of incorrect ratings, feedback scores are not fully reliable [18,20]. In essence, some users may try to increase their feedback scores with deceptive means [24].…”

Section: Related Workmentioning

confidence: 99%

Incremental collusive fraud detection in large-scale online auction networks

et al. 2020

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An online auction network (OAN) is a community of users who buy or sell items through an auction site. Along with the growing popularity of auction sites, concerns about auction frauds and criminal activities have increased. As a result, fraud detection in OANs has attracted renewed interest from researchers. Since most real OANs are large-scale networks, detecting fraudulent users is usually difficult, especially when multiple users collude with each other and new online auctions are continuously added. Although collusive auction frauds are not as popular as other types of auction frauds, they are more horrible and catastrophic because they often bring huge financial losses. To tackle this issue, some techniques have been proposed to detect collusive frauds in OANs. While all of the techniques have demonstrated promising results, they often suffer from low detection performance or slow convergence, especially in large-scale OANs. In this paper, we overcome these deficiencies by presenting ICAFD, a novel technique that recasts the problem of detecting collusive frauds in large-scale OANs as an incremental semi-supervised anomaly detection problem. In this technique, we propagate reputations from a small set of labeled benign users to unlabeled users along the auction relationships between them and then incrementally update reputations when a new auction gets added to the OAN. This increases the convergence of ICAFD and allows it to avoid wasteful recalculation of reputations from scratch. Our experimental results show that ICAFD can successfully detect different types of collusive auction frauds in a reasonable detection time.

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Feedback based Trust Management for Cloud Environment

Cited by 10 publications

References 20 publications

A new trust management framework based on the experience of users in industrial cloud computing using multi-criteria decision making

A new trust management framework based on the experience of users in industrial cloud computing using multi-criteria decision making

Trustworthy Cloud Computing

Incremental collusive fraud detection in large-scale online auction networks

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