Dynamic Trust Model Based on Service Recommendation in Big Data

• 作者: Gang Wang Mengjuan Liu
• 来源期刊: 计算机、材料和连续体(英文)
• 学科: 工学
• 关键词: TRUST model RECOMMENDATION TRUST CONTENT SIMILARITY ONTOLOGY BIG data.
• 年，卷（期）: 2019,（3）
• 页码范围: 845-857
• 页数: 13页
• 分类号: TP3

摘要

In big data of business service or transaction,it is impossible to provide entire information to both of services from cyber system,so some service providers made use of maliciously services to get more interests.Trust management is an effective solution to deal with these malicious actions.This paper gave a trust computing model based on service-recommendation in big data.This model takes into account difference of recommendation trust between familiar node and stranger node.Thus,to ensure accuracy of recommending trust computing,paper proposed a fine-granularity similarity computing method based on the similarity of service concept domain ontology.This model is more accurate in computing trust value of cyber service nodes and prevents better cheating and attacking of malicious service nodes.Experiment results illustrated our model is effective.