Biblio

Nowadays, network information security is of great concern, and the measurement of the trustworthiness of terminal devices is of great significance to the security of the entire network. The measurement method of terminal device security trust still has the problems of high complexity, lack of universality. In this paper, the device fingerprint library of device access network terminal devices is first established through the device fingerprint mixed collection method; Secondly, the software and hardware features of the device fingerprint are used to increase the uniqueness of the device identification, and the multi- dimensional standard metric is used to measure the trustworthiness of the terminal device; Finally, Block chain technology is used to store the fingerprint and standard model of network access terminal equipment on the chain. To improve the security level of network access devices, a device access method considering the trust of terminal devices from multiple perspectives is implemented.

In this paper, we propose a hybrid collaborative filtering recommendation algorithm based on heuristic similarity and trust measure, in order to alleviate the problem of data sparsity, cold start and trust measure. Firstly, a new similarity measure is implemented by weighted fusion of multiple similarity influence factors obtained from the rating matrix, so that the similarity measure becomes more accurate. Then, a user trust relationship computing model is implemented by constructing the user's trust network based on the trust propagation theory. On this basis, a SIMT collaborative filtering algorithm is designed which integrates trust and similarity instead of the similarity in traditional collaborative filtering algorithm. Further, an improved K nearest neighbor recommendation based on clustering algorithm is implemented for generation of a better recommendation list. Finally, a comparative experiment on FilmTrust dataset shows that the proposed algorithm has improved the quality and accuracy of recommendation, thus overcome the problem of data sparsity, cold start and trust measure to a certain extent.

To this date the majority of the existing instruments to measure trustworthiness in an online context are based on Likert scaling [1,3,11]. These however are somewhat restricted in applicability. Statements formed in Likert scaling are typically addressing one specific website. Therefore, adjusting these statements for other websites can be accompanied with a loss of validity. To meet these limitations, we propose to use semantic differential. Research has shown that using semantic differential is appropriate to measure multidimensional constructs [8,12] such as trust. Our novel approach in measuring trustworthiness exceeds Likert based scaling in its effortless application in different online context and its better translatability. After one pre-study and two online-studies with a total of 554 participants we achieved to develop a questionnaire with nine items which is comparable to other existing questionnaires in terms of reliability and internal consistency. But it overcomes the limitation of Likert scale based questionnaire.