<span class="var-sub_title">Social Computational Trust Model (SCTM): A Framework to Facilitate Selection of Partners</span> SC18 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

Innovating the Network for Data Intensive Science (INDIS)


Social Computational Trust Model (SCTM): A Framework to Facilitate Selection of Partners

Abstract: Creating a cyber security alliance among network domain owners, as a means to minimize security incidents, has gained the interest of practitioners and academics in the last few years. A cyber security alliance, like any membership organization, requires the creation and maintenance of trust among its members, in this case the network domain owners. To promote the disclosure and sharing of cyber security information among the network domain owners, a trust framework is needed.

This paper discusses a social computational trust model (SCTM), that helps alliance members to select the right partner to collaborate with and perform collective tasks, and encourages the sharing of incident data and intelligence. The social computational trust model combines benevolence and competence to estimate the risk of interaction. Benevolence is computed from personal experiences gained through direct interactions and competence is assessed on the base of the received feedback from the other members. An agent based model case study is presented to demonstrate our approach. The practicability of the proposed risk estimation is validated with a detailed experiment.


Archive Materials


Back to Innovating the Network for Data Intensive Science (INDIS) Archive Listing

Back to Full Workshop Archive Listing