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.

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 assessment 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 significance for ensuring the cloud service trustworthiness and improving the cloud service market security.

We present a simple design technique for extended irregular repeat-accumulate (eIRA) codes for flat Rayleigh fading channels, using simple channels as surrogates in the design. We show that eIRA codes designed for the burst-erasure channel (BuEC) or the burst-erasure channel with AWGN (BuEC-G) achieve essentially the same performance over Rayleigh fading channels as codes designed for the fading channel. Thus, to design good codes for Rayleigh fading channels, instead of implementing the complex design procedures targeted, specifically for this channel, we propose the simple approach of designing codes over surrogate channels, the BuEC or the BuEC-G. We also show that eIRA codes designed for the BuEC enjoy the advantage of efficient encodability and a lower error-rate floor. Finally, we demonstrate that it is the distribution of the number of faded bits per codeword which determines the difference between correlated and uncorrelated fading channel performance. Perfect channel state information is assumed in this paper.

To obtain precise personalized services in mobile commerce, the users have to disclose their personal information to the operator, which constitutes a potential threat to their privacy security. In this paper, a mobile commerce privacy security risk assessment model is established based on information entropy and Markov chain, and effective security risk measurement, and assessment method is put forward. Our method can provide accurate and quantitative results in assessing privacy disclosure risk to guide the users’ selection of safe mobile commerce applications and protect their privacy security.

Perceived trust is a key factor affecting the behavior to donate online. In order to further explore the factors and influencing mechanisms that affect the success of medical crowdfunding projects, this paper, combined with the Stimulus-Organism-Response (S-O-R) theory, introduces the mediating variable of social presence and perceived differences in trust, and constructs a model of online users’ donation behavior to medical crowdfunding projects. We collected 437 valid samples through a questionnaire survey, and processed the data with SPSS and Amos software to test and analyze the theoretical model. The research results showed that project description and user participation have a significant positive effect on social presence; project transparency and patient identity have a significant negative effect on perceived differences in trust; social presence has a positive effect on donation behavior, while the perceived difference in trust has a negative effect; social presence and perceived differences in trust play a mediating role respectively; there is no significant effect of patient status on social presence. This study further expands the application of social presence and perceived differences in trust in medical crowdfunding, and provides a theoretical basis for the success of medical crowdfunding projects.

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.