Guest Editorial IEEE Transactions on Emerging Topics in Computing Special Section on Advances in Emerging Privacy-Preserving Computing

被引：0

作者：

Han, Jinguang ^{[1
]}

Schaumont, Patrick ^{[2
]}

Susilo, Willy ^{[3
]}

机构：

[1] Southeast Univ, Sch Cyber Sci & Engn, Nanjing 210096, Jiangsu, Peoples R China

[2] Worcester Polytech Inst, Comp Engn, Worcester, MA 01609 USA

[3] Univ Wollongong, Sch Comp & Informat Technol, Fac Engn & Informat Sci, Wollongong, NSW 2522, Australia

来源：

IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING | 2024年 / 12卷 / 01期

关键词：

Special issues and sections; Homomorphic encryption; Privacy; Machine learning; Machine learning algorithms; Training data; Memory; Intelligent systems; Cloud computing;

D O I：

10.1109/TETC.2024.3374568

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Machine learning and cloud computing have dramatically increased the utility of data. These technologies facilitate our life and provide smart and intelligent services. Notably, machine learning algorithms need to learn from massive training data to improve accuracy. Hence, data is the core component of machine learning and plays an important role. Cloud computing is a new computing model that provides on-demand services, such as data storage, computing power, and infrastructure. Data owners are allowed to outsource their data to cloud servers, but will lose direct control of their data. The rising trend in data breach shows that privacy and security have been major issues in machine learning and cloud computing.

引用

页码：266 / 268

页数：3