Toward Risk Reduction for Mobile Service Composition

Deng, Shuiguang; Huang, Longtao; Liu, Ying; Zhou, Honggeng; Wu, Zhaohui; Cao, Xiongfei; Kataev, Mikhail Yu.; Li, Ling

doi:10.1109/tcyb.2015.2446443

Cited by 29 publications

(10 citation statements)

References 42 publications

(31 reference statements)

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“…The problem in [20] is its high computation time along with its weak protection to the secret random value, since its encrypted by employing the current time as a key. Another scheme proposed by Deng et al [21] had employed bilinear pairing and data aggregation that can be recovered by the cloud center.…”

Section: Related Workmentioning

confidence: 99%

A Lightweight and Secure Anonymity Preserving Protocol for WBAN

Almuhaideb

Alqudaihi

2020

IEEE Access

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In the medical fields, wearable body area sensors network (WBAN) is playing a major role in maintaining user health by providing convenience service for the patient and doctors. However, sensor data transmission in an insecure communication channel enables the attacker from tampering the sensor data, disguising as a legitimate user, or intercepting the forwarded packets from its unprotected sources. A wide variety of secure authentication schemes were proposed to improve the communicated channels' reliability in protecting the user data. Moreover, those schemes are lacking the guarding of nodes anonymity, key management, and size. Thence, we propose a lightweight WBAN authentication with two protocols P-I for authentication and P-II for re-authentication to protect the nodes anonymity and increase the efficiency. Furthermore, our scheme employed better key management with high randomness of the security parameters to provide higher protection as a trade-off between security and efficiency. The scheme formal proof for the key agreement and mutual authentication is conducted through (Burrows Abadi Nadeem) BAN logic.

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Section: Related Workmentioning

confidence: 99%

A Lightweight and Secure Anonymity Preserving Protocol for WBAN

Almuhaideb

Alqudaihi

2020

IEEE Access

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“…Driven by perceived real-time energy and production efficiency information, an enhanced Pareto-based bees algorithm is proposed to improve the sustainability of manufacturing equipment services [18]. Deng et al proposes a risk model and clarifies the risk of mobile service composition; and then proposes a service composition approach by modifying the simulated annealing algorithm [19]. A hybrid Genetic Algorithm is proposed to solve the bi-objective optimization problem from both economic and ecological perspectives [20].…”

Section: Related Workmentioning

confidence: 99%

“…The constraint (18) denotes that only one service should be selected to complete a subtask, and the constraint (19) means that the consumer cost cannot exceed the budget. The constraint (20) indicates that the delivery time are less than the time constraint.…”

Section: Objectives and Constraintsmentioning

confidence: 99%

Long/Short-Term Utility Aware Optimal Selection of Manufacturing Service Composition Toward Industrial Internet Platforms

Zhang

Tao

Liu

et al. 2019

IEEE Trans. Ind. Inf.

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As numerous Industrial Internet platforms emerge, manufacturing services are shared among multiple stakeholders more frequently than ever before. The optimal selection of shared manufacturing service composition (MSC) should promise both the task completion and the stakeholders' satisfaction. However, as commercial entities, stakeholders concentrate on not only the temporary benefits but also the long-term acquisitions. Most of the existing MSC problems neglect the stakeholders' prospect on the manufacturing service sharing. This leads to the disappointment and dissatisfaction of the stakeholders with long-term expectations, who will abandon the participation in Industrial Internet platform. Therefore, the long/short-term preferences of various stakeholders should be satisfied and balanced. In this paper, the long/short-term utility and preferences of three parties (provider, consumer, and operator) are first defined and discussed, and the models considering short-term utility of a consumer and long-term utility of providers are established. The potential tasks assigned to providers are taken into account to estimate the long-term utility if the current task is accepted. Then, to solve the bi-objective optimization problem, an improved Non-dominated Sorting Genetic Algorithm-II algorithm, combining Tabu search and improved K-means mechanism, is proposed to find the optimal solution set. Finally, the effectiveness of the method is verified by the experimental results in terms of solution diversity, astringency and stability, in which a finding is further observed that the changes of consumers' preferences have little impact on the long-term utility of providers.

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“…They try to compute the utility of a mashup from the utilities of its component services, and derive the constraints of component services from the constraints of the objective service mashups. Besides, we have addressed the problem of service selection in mobile environment, considering different optimization objectives including response time [23,24], energy consumption [24,25], and risk reduction [26].…”

Section: Related Workmentioning

confidence: 99%

Cost Performance Driven Service Mashup: A Developer Perspective

Deng

Taheri

et al. 2016

IEEE Trans. Parallel Distrib. Syst.

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Service mashups are applications created by combining single-functional services (or APIs) dispersed over the web. With the development of cloud computing and web technologies, service mashups are becoming more and more widely used and a large number of mashup platforms have been produced. However, due to the proliferation of services on the web, how to select component services to create mashups has become a challenging issue. Most developers pay more attention to the QoS (quality of service) and cost of services. Beside service selection, mashup deployment is another pivotal process, as the platform can significantly affect the quality of mashups. In this paper, we focus on creating service mashups from the perspective of developers. A genetic algorithm-based method, GA4MC (genetic algorithm for mashup creation), is proposed to select component services and deployment platforms in order to create service mashups with optimal cost performance. A series of experiments are conducted to evaluate the performance of GA4MC. The results show that the GA4MC method can achieve mashups whose cost performance is extremely close to the optimal. Moreover, the execution time of GA4MC is in a low order of magnitude and the algorithm performs good scalability as the experimental scale increases.

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Toward Risk Reduction for Mobile Service Composition

Cited by 29 publications

References 42 publications

A Lightweight and Secure Anonymity Preserving Protocol for WBAN

A Lightweight and Secure Anonymity Preserving Protocol for WBAN

Long/Short-Term Utility Aware Optimal Selection of Manufacturing Service Composition Toward Industrial Internet Platforms

Cost Performance Driven Service Mashup: A Developer Perspective

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