Efficient Web APIs Recommendation With Privacy-Preservation for Mobile App Development in Industry 4.0

被引：25

作者：

Gong, Wenwen ^{[1
]}

Zhang, Wei ^{[2
]}

Bilal, Muhammad ^{[3
]}

Chen, Yifei ^{[1
]}

Xu, Xiaolong ^{[4
]}

Wang, Weizheng ^{[5
]}

机构：

[1] China Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China

[2] Weifang Univ Sci & Technol, Weifang Key Lab Blockchain Agr Vegetables, Weifang 262700, Peoples R China

[3] Hankuk Univ Foreign Studies, Dept Comp Engn, Yongin 17035, South Korea

[4] Nanjing Univ Informat Sci & Technol, Sch Comp & Software, Nanjing 210044, Peoples R China

[5] City Univ Hong Kong, Dept Comp Sci, Hong Kong, Peoples R China

来源：

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS | 2022年 / 18卷 / 09期

基金：

中国国家自然科学基金;

关键词：

Industrial Internet of Things; Mobile applications; Privacy; Informatics; Indexes; Fourth Industrial Revolution; Steiner trees; App development; efficiency; Industry; 4; 0; privacy; web APIs recommendation;

D O I：

10.1109/TII.2021.3133614

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Integrating lightweight web application programming interfaces (APIs) into mobile Apps is a promising way for quick and cost-effective development of mobile Apps with desired functions. Web APIs, on the other hand, are created by distinct enterprises or organizations, making it challenging to develop compatible and diverse mobile Apps by combining existing web APIs. It has been demonstrated that this process is an NP-hard problem. In mobile Apps development, it is often necessary to read confidential information, leading to the business privacy leakage of enterprises. Thus, we devise a novel efficient web APIs recommendation (E-WAR) approach based on locality-sensitive hashing for recommending desirable web APIs to developers. Through analyzing industrial enterprises' expected needs, E-WAR efficiently makes compatible and diverse web APIs recommendations while guaranteeing privacy protection. Finally, extensive experiments on real-world web APIs datasets are conducted. The results show that E-WAR can achieve significant performance improvements over the existing approaches.

引用

页码：6379 / 6387

页数：9

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