ARIMA Model-Based Web Services Trustworthiness Evaluation and Prediction

Meng Li, Zhebang Hua, Junfeng Zhao, Yanzhen Zou, Bing Xie

Abstract: As most Web services are delivered by third parties over unreliable Internet and are late bound at run-time, it is reasonable and useful to evaluate and predict the trustworthiness of Web services. In this paper, we propose an ARIMA model-based approach to evaluate and predict Web services trustworthiness. First, we evaluate Web services trustworthiness with comprehensive trustworthy evidences collected from the Internet on a regular basis. Then, the cumulative trustworthiness evaluation records are modeled as time series. Finally, we propose an ARIMA model-based multi-step Web services trustworthiness prediction process, which can automatically and iteratively identify and optimize the model to fit the trustworthiness series data. Experiments conducted on a large-scale real-world data set show that our method can effectively evaluate and predict the trustworthiness of Web services, which helps users to reuse Web services.