Extension of Subjective Logic for Time-Related Trust

To describe the dynamic propcrty of trust relationship, wt propose atime-related trust model and extend Joang's subjective logic to fit for time-related trust model.The extension includes prepositional conjunction, disjunction and negation for traditional logic anddiscounting and consensus operators that are evidential operators specially designed for thepropagation and computation of trust relationships. With the extension of subjective logic fortime-related trust, our time-related trust modelis suitable to model the dynamic trust relationshipin practice. Finally an example of reputation assessment is offered to demonstrate the usage of ourtrust model.

TRUST MODEL BASED ON THE MULTINOMIAL SUBJECTIVE LOGIC AND RISK MECHANISM FOR P2P NETWORK OF FILE SHARING

In order to deal with the problems in P2P systems of file sharing such as unreliability of the service,security risk and attacks caused by malicious peers,a novel Trust Model based on Multinomial subjective logic and Risk mechanism(MR-TM) is proposed.According to the multinomial subjective logic theory,the model introduces the risk mechanism.It assesses and quantifies the peers' risk,through computing the resource value,vulnerability,threat level,and finally gets the trust value by the risk value and the reputation value.The introduction of the risk value can reflect the recent behaviors of the peers better and make the system more sensitive to malicious acts.Finally,the effectiveness and feasibility of the model is illustrated by the simulation experiment designed with Peersim.

Comparison-embedded evidence-CNN model for fuzzy assessment of wear severity using multi-dimensional surface images

Wear topography is a significant indicator of tribological behavior for the inspection of machine health conditions.An intelligent in-suit wear assessment method for random topography is here proposed.Three-dimension(3D)topography is employed to address the uncertainties in wear evaluation.Initially,3D topography reconstruction from a worn surface is accomplished with photometric stereo vision(PSV).Then,the wear features are identified by a contrastive learning-based extraction network(WSFE-Net)including the relative and temporal prior knowledge of wear mechanisms.Furthermore,the typical wear degrees including mild,moderate,and severe are evaluated by a wear severity assessment network(WSA-Net)for the probability and its associated uncertainty based on subjective logic.By integrating the evidence information from 2D and 3D-damage surfaces with Dempster–Shafer(D–S)evidence,the uncertainty of severity assessment results is further reduced.The proposed model could constrain the uncertainty below 0.066 in the wear degree evaluation of a continuous wear experiment,which reflects the high credibility of the evaluation result.

Using New Fusion Operations to Improve Trust Expressiveness of Subjective Logic

Subjective logic provides a means to describe the trust relationship of the realworld. However, existing fusion operations it offers Weal fused opiniotts equally, which makes it impossible to deal with the weighted opinions effectively. A. Jcsang presents a solution, which combines the discounting operator and the fusion operator to produce the consensus to the problem. In this paper, we prove that this approach is unsuitable to deal with the weighted opinions because it increases the uncertainty of the consensus. To address the problem, we propose two novel fusion operators that are capable of fusing opinions according to the weight of opinion in a fair way, and one of the strengths of them is improving the trust expressiveness of subjective logic. Furthermore, we present the justification on their definitions with the mapping between the evidence space and the opinion space. Comparisons between existing operators and the ones we proposed show the effectiveness of our new fusion operations.