The popularity of cloud computing has made cloud services gradually become the leading computing model nowadays. The trustworthiness of cloud services depends mainly on construction processes. The trustworthiness measurement of cloud service construction processes (CSCPs) is crucial for cloud service developers. It can help to find out the causes of failures and to improve the development process, thereby ensuring the quality of cloud service. Herein, firstly, a trustworthiness hierarchy model of CSCP was proposed, and the influential factors of the processes were identified following the international standard ISO/IEC 12207 of the software development process.Further, a method was developed combined with the theory of information entropy and the concept of trustworthiness. It aimed to calculate the risk uncertainty and risk loss expectation affecting trustworthiness. Also, the trustworthiness of cloud service and its main construction processes were calculated. Finally, the feasibility of the measurement method were verified through a case study, and through comparing with AHP and CMM/CMMI methods, the advantages of this method were embodied. Carnegie-Mellon University and the National Defense Industry Association. The two models classified the development stages of software organizations in practice as defining, implementing, measuring, controlling and improving software products. However, only a framework was put forward, extracting no specific knowledge of each key process area and failing to quantify the quality of a specific process. Also, the two models are primarily used to evaluate the degree of process management practices of a development organization, involving many contents, and being time-consuming and costly. As a result, small and medium-sized software companies, even some large ones, face challenges to meet relevant requirements and standards. For most software development organizations, what they need is an objective, quantitative, real and easy-to-implement measurement method. The method should enable them to find the weak links in the cloud service construction process (CSCP), and then carry out subsequent improvement or reinforcement, thus reducing the probability of institutional failure and improving product quality. Other primary software process measurement methods include Goal-driven Software Measurement (GSM) [7], Practical software measurement (PSM) [8,9], and Statistical Process Control (SPC) [10]. Based on the characteristics of the CMM and GQM model [11], reference [12] established a software process framework supporting metrics and gave the metrics of software process improvement. However, it did not give the exact measurement steps for the software development process. Reference [13] discussed the significant problems in software process measurement and presented an active measurement model (AMM) to support software process improvement (SPI). It emphasized the measurement of quality, maintainability and stability of the software products, rather than the processes. To find the pro...
Epidemic risk has great uncertainty and harmfulness, which poses a potential threat to public health in a certain region. Establishing a special risk assessment system to assess and predict the potential epidemic risk of a region can effectively avoid or reduce the impact of epidemic risk. Therefore, this paper combs the related factors that affect the epidemic risk, and proposes an epidemic risk assessment model based on 12 indicators by combining Markov chain and AHP. The model can assess the epidemic situation in a certain region from four aspects: the probability of risk occurrence, the probability of loss, the possibility of risk disappearance and risk duration, so as to provide detailed data for the risk management and control of epidemic in the region, and help the epidemic prevention work to be carried out in a targeted way. Finally, the case analysis and method comparison are carried out,and the results show that the model proposed in this paper is reasonable and feasible.
As an indispensable medium for people’s daily life and communication, mobile applications provide users with a variety of services. In order to enjoy these services, users inevitably need to provide personal privacy information or authorization to application providers in the process of use. In the case of insufficient privacy security evaluation, even if users use the applications verified by the application market, their privacy security will be threatened because of their weak awareness of privacy protection. Therefore, in order to ensure the privacy security of users, this paper establishes a mobile service assessment attribute model including 3 risk categories and 11 risk indicators. Based on this model, this paper proposes a service risk weight assessment method based on FAHP (fuzzy analytical hierarchy process), defines the risk level and its trust degree from two aspects of risk frequency and risk loss, and puts forward a reasonable fusion method for different assessment results of risk level based on D–S (Dempster–Shafer) theory, so as to realize the multidimensional and multilayer assessment of mobile service risk. Finally, the case analysis shows that the method proposed in this paper is reasonable and feasible and has important value for improving the security of mobile services and managing users’ privacy information.
With the development and popularization of cloud computing technology, more and more users choose cloud services to build their application systems. With the improvement of users’ understanding of software systems, in addition to functionality, trustworthiness has become another key issue concerned by users. Based on the existing research on cloud service trustworthiness measurement and evaluation, this paper proposes a cloud service-trusted delivery model based on asymmetric encryption and hash function and a trusted runtime model of cloud service system based on block chain technology. The proposed models will effectively solve the untrusted problems such as denial and tampering in the process of cloud service acquisition, as well as the system anomaly at runtime. Finally, through targeted experiments to verify the effectiveness and feasibility of the proposed models, and through experimental analysis, this paper expounds on the principle and mechanism of model operation and trustworthiness guarantee.
The massive cloud service market is full of various services with uneven quality. Even the services that have passed the platform detection will have unknown trustworthiness problems in the actual use process. The risk environment of the cloud service determines that its trustworthiness is random. The static trustworthiness assessment results can only reflect the cloud service trustworthiness at a certain time, not enough to reflect the real trustworthiness of the cloud service. To objectively reflect the trustworthiness of the cloud service, it is necessary to further assess the cloud service trustworthiness state and its changes on the basis of trustworthiness level measurement. To solve this problem, this paper combs the trustworthiness indicators of the cloud service, puts forward an effective assessment method of cloud service trustworthiness level based on D-S theory, and puts forward the representation method of cloud service trustworthiness state and its transition state combined with Markov chain, so as to realize the effective assess of cloud service trustworthiness state and its changes. Finally, through case analysis, it shows that the method proposed in this paper is feasible, can effectively assess the cloud service trustworthiness state and its changes, and provide users with detailed assessment results, so as to help users make reasonable service selection and trustworthiness management. This research has important research significance for ensuring the trustworthiness of the cloud service and improving the security of cloud service market.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.