Fuzzy Based Trust Management System for Cloud Environment

Kumar, Sunil; Mittal, Sumit; Singh, Manpreet

doi:10.12913/22998624/62703

Cited by 11 publications

(6 citation statements)

References 11 publications

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“…In the study by Kumar et al [36], a fuzzy-based trust management system was proposed to facilitate cloud service delivery and identify trusted providers. e proposed system simulation showed that the degree of reliability and trust of the proposed system was higher compared with that of other CSPs.…”

Section: Related Workmentioning

confidence: 99%

Fuzzy Rule-Based Trust Management Model for the Security of Cloud Computing

Soleymani

Abapour

Taghizadeh

et al. 2021

Mathematical Problems in Engineering

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In the last few years, due to the benefit of solving large-scale computational problems, researchers have been developed multicloud infrastructures. The trust-related issue in multiclouds includes more complicated content and new problems. A new trust management framework for multicloud environments is proposed in this article. The proposed framework used a combination of objective and subjective trust values to calculate the cloud service provider’s trust values. This new framework can identify and rectify fake feedbacks from other feedbacks. Another advantage of this framework is applying fuzzy rules to calculate trust values. Two main components of the proposed framework are simulated in this paper. The simulation results confirm the important role of applied components. Also, this paper proposed a framework compared with other frameworks (feedback-based model, SLA-based model, and multicloud model). Simulation results show the proposed framework increased trust values rather than other models. Also, compared with other models, our framework gives better mean trust values.

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Section: Related Workmentioning

confidence: 99%

Fuzzy Rule-Based Trust Management Model for the Security of Cloud Computing

Soleymani

Abapour

Taghizadeh

et al. 2021

Mathematical Problems in Engineering

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“…Moreover, the combination of Mamdani and Sugeno fuzzy inference systems in their study would deem inconsistent and no apparent advantage is elaborated with the use of both. On the other hand, for work in [28], the trust value for each CSP is based on four basic parameters namely security, availability, cost and performance. However, since the metrics are evaluated separately, it cannot be confirmed that the trust values would correctly represent the exact condition of the CSP compared to if these metrics are evaluated together.…”

Section: Trust Evaluation Using Fuzzy Logicmentioning

confidence: 99%

“…To develop an overall measure of trust value of the cloud providers, [30] uses Seguno fuzzy technique to process four criteria; scalability, availability, security, usability. Unlike the works in [27] and [28], study in [30] has evaluated all the metrics together but explanation of how each of the criteria are quantified is lacking in all of the works mentioned above.…”

Section: Trust Evaluation Using Fuzzy Logicmentioning

confidence: 99%

Find my trustworthy fogs: A fuzzy-based trust evaluation framework

Rahman

Newaz

et al. 2020

Future Generation Computer Systems

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Find My Trustworthy Fogs: A Fuzzy-based Trust Evaluation Frameworkhttp://researchonline.ljmu.ac.uk/id/eprint/8724/ Article LJMU has developed LJMU Research Online for users to access the research output of the University more effectively. AbstractThe growth of IoT is proven with the massive amount of data generated in 2015, and expected to be even more in the years to come. Relying on the cloud to meet the expanding volume, variety, and velocity of data that the IoT generates may not be feasible. In the last two years, fog computing has become a considerably important research topic in an attempt to reduce the burden on cloud and solve cloud's inability to meet the IoT latency requirement. However, fog environment is different than in cloud since fog environment is far more distributed. Due to the dynamic nature of fog, backups such as redundant power supply would deem unnecessary, and relying on just one Internet Service Provider for their fog device would be sufficient. If obstacles arise in this fog environment, factors such as latency, availability or reliability would in turn be unstable. Fogs become harder to trust, and this issue is more complicated and challenging in comparison to the conventional cloud. This implies that trustworthiness in fog is an imperative issue that needs to be addressed. With the help of a broker, managing trust in a distributive environment can be tackled. Acting as an intermediary, a broker helps in facilitating negotiation between two parties. Although the brokering concept has been around for a long time and is widely used in the cloud, it is a new concept in fog computing. As of late, there are several research studies that incorporates broker in fog where these brokers focus towards pricing management. However to the best of our knowledge there is no literature on broker-based trust evaluation in fog service allocation. This is the first work that proposes broker-based trust evaluation framework that focuses on identifying a trustworthy fog to fulfill the user requests. In this paper, fuzzy logic is used as the basis for the evaluation while considering the availability and cost of fog. We propose Request Matching algorithm to identify a user request, and Fuzzybased Filtering algorithm to match the request with one of the predefined sets created and managed by the broker. In this paper, we present a use case that illustrates how fuzzy logic works in determining the trustworthiness of a fog. Our findings suggest that the algorithms can successfully provide users a trustworthy fog that matches their requirement. .bn (Wida Susanty Suhaili), g.m.lee@ljmu.ac.uk (Gyu-Myoung Lee)

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“…Conductive polymer being a popular topic discussion among the researchers since its discovery in late 1970 due to of its unique properties and features. Since then, research activities on conductive polymer has increased rapidly, which is indicated by the large number of research results reported through several publications [1,2]. Polyaniline (PANi) is one of the conductive polymer which received much attention and being developed intensively because of their simple preparation and less costly in production costs when compared with that of other groups [3].…”

Section: Introductionmentioning

confidence: 99%

“…Because of such unique properties, a lot of research and development of conducting polymeric materials based on PANi are directed towards the use of PANi in various applications [4]. There have been some routes in preparation of PANi, a few to mention is a chemical oxidation reaction [1], electrochemical method [5] and vacuum deposition technique [6]. Some improved synthesis methods of PANi have been introduced to improve and increase the properties of PANi like electrical conductivity value, heat resistance, etc.…”

Section: Introductionmentioning

confidence: 99%

The Role of Anionic Surfactant to the Particle Size Reduction of Conductive PANi

Hafizah

Mahar

Suparno

et al. 2020

MSF

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The conductive polyaniline (PANi) with fine particles of sizes from 724 nm down to 191 nm has been successfully synthesized through chemical oxidation reaction. The synthesis of PANi was carried out in acidic media under HCl 1.5 M solution using ammonium persulphate (APS) as an oxidizing agent in the presence of anionic surfactants. Two different types of surfactant respectively Sodium Octyl Sulphate (SOS) and Sodium Dodecyl Sulphate (SDS) were brought into an investigation on the effect of the surfactant chain length of C8 and C12 to the particle size formation. Such molecular chain length is responsible for the particle size growth rate. It was found that the average particle size of PANi decreased gradually by the addition of SOS and SDS surfactants with 1 % concentration each. The particle of PANi with sizes 296 nm and 191 nm was obtained as analyzed by Particle Size Analyzer (PSA). These sizes are far below 724 nm, which obtained from the same reaction but with surfactant free. Other supporting indicators showed that the pH of reaction solution was somewhat more acidic after 7 hours of reaction when the surfactant with pH value range within 0.7 – 1.4 presence. The temperature of solution increased with time following the energy released reached 30-31°C within the first 30 minutes, which was lower when compared with that of surfactant free.

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Fuzzy Based Trust Management System for Cloud Environment

Cited by 11 publications

References 11 publications

Fuzzy Rule-Based Trust Management Model for the Security of Cloud Computing

Fuzzy Rule-Based Trust Management Model for the Security of Cloud Computing

Find my trustworthy fogs: A fuzzy-based trust evaluation framework

The Role of Anionic Surfactant to the Particle Size Reduction of Conductive PANi

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