WSN and IoT

14Privacy-Preserving Machine Learning on Non-Co-Located Datasets Using Federated LearningChallenges and Opportunities

Jyoti L, Bangare, Nilesh P. Sable, Parikshit N. Mahalle and Gitanjali Shinde

DOI: 10.1201/9781003437079-14

14.1 Introduction

In the age of big data and distributed computing, it is becoming more common to find datasets that are not physically located in the same location. Since these datasets are spread across several locations (i.e. they are non-co-located) and are hosted by diverse organizations, combining and analyzing them presents a variety of difficulties. Recent developments in ML methods, particularly federated learning, provide interesting new options for overcoming these difficulties while preserving the confidentiality ...