SelfTrust:leveraging self-assessment for trust inference in Internetware  

作　　者：YAO Yuan XU Feng REN YongLi TONG HangHang L Jian 

机构地区：[1]State Key Laboratory for Novel Software Technology [2]Department of Computer Science and Technology, Nanjing University [3]School of Information Technology, Deakin University [4]City College, City University of New York

出　　处：《Science China(Information Sciences)》2013年第10期212-225,共14页中国科学（信息科学）（英文版）

基　　金：supported by National Natural Science Foundation of China(Grant Nos.91318301,60736015,61073030);National High-tech R&D Program of China(863 Program)(Grant No.2012AA011205);National Basic Research Program of China(973 Program)(Grant No.2009CB320702)

摘　　要：Abstract Internetware is envisioned as a new software paradigm for software development in platforms such as the Internet. The reliability of the developed software becomes a key challenge due to the open, dynamic and uncertain nature of such environment. To make the development more reliable, it is necessary to evaluate the trustworthiness of the resource providers or potential working partners. To this end, we propose a novel trust inference approach to evaluating the trustworthiness of potential partners to guide the software development in Internetware. The main insight of our approach is to employ the self-assessment information in order to improve the trust inference accuracy. Especially, we first extend the balance theory and the status theory from social science to incorporate self-assessment, and then propose a machine learning framework to extract several features from the extended theories and infer trustworthiness scores based on these features. Experimental results on a real software developer network show that the self-assessment information truly helps to improve the accuracy of trust inference, and the proposed SelfTrust model is more accurate than other state-of-the-art methods.Abstract Internetware is envisioned as a new software paradigm for software development in platforms such as the Internet. The reliability of the developed software becomes a key challenge due to the open, dynamic and uncertain nature of such environment. To make the development more reliable, it is necessary to evaluate the trustworthiness of the resource providers or potential working partners. To this end, we propose a novel trust inference approach to evaluating the trustworthiness of potential partners to guide the software development in Internetware. The main insight of our approach is to employ the self-assessment information in order to improve the trust inference accuracy. Especially, we first extend the balance theory and the status theory from social science to incorporate self-assessment, and then propose a machine learning framework to extract several features from the extended theories and infer trustworthiness scores based on these features. Experimental results on a real software developer network show that the self-assessment information truly helps to improve the accuracy of trust inference, and the proposed SelfTrust model is more accurate than other state-of-the-art methods.

关 键 词：trust inference SELF-ASSESSMENT balance theory status theory INTERNETWARE 

分 类 号：TP393.0[自动化与计算机技术—计算机应用技术]