Federated Learning (FL) is a new technology that has been a hot research topic. It enables training an algorithm across multiple decentralized edge devices or servers holding local data samples, without exchanging them. There are many application domains where large amounts of properly labeled and complete data are not available in a centralized location, for example, doctors' diagnosis from medical image analysis. There are also growing concerns over data and user privacy as Artificial Intelligence is becoming ubiquitous in new application domains. As such, very recently, a lot of research has been conducted in several areas within the nascent field of FL. A variety of surveys on different subtopics exist in current literature, focusing on specific challenges, design aspects and application domains. In this paper, we review existing contemporary works in the related areas in order to understand the challenges and topics that are emphasized by each type of FL surveys. Furthermore, we categorize FL research in terms of challenges, design factors and applications, conducting a holistic review of each and outlining promising research directions.

Identity Management System (IDMS) refers to how users or individuals are identified and authorized to use organizational systems and services. Since traditional identity management and authentication systems rely heavily on a trusted central authority, they cannot mitigate the effects of single points of failure. As a decentralized and distributed public ledger in a peer-to-peer (P2P) network, Blockchain (BC) technology has garnered a considerable amount of attention in the field of IDMS in recent years. Through Self-Sovereign Identity (SSI), users can have full authority over their digital identity. Successful implementation of a BC-based IDMS can significantly increase the degree of privacy and security of a user's SSI. However, the integration of BC-based IMDS to provide a user with SSI is still an unorganized area of research in its early stages of development. This article presents an extensive literature review of state-of-the-art academic publications as well as commercial market offerings regarding the applicability of BC-based SSI solutions. It also provides a detailed preliminary regarding the building blocks of blockchain technology and a progressive roadmap of IDMS solutions. In order to develop an effective BC-based IDMS solution that focuses on securing a user's SSI, this article outline five essential components of a BC-based IDMS: authentication, integrity, privacy, trust, and simplicity. Furthermore, we perform a security analysis that outlines several types of adversarial threats that can cause potential damage to the BC-based IDMS. We identify and discuss associated issues and challenges by analyzing several notable BC-based IDMS solutions in academic literature. We also highlight potential research gaps and provide future research scope.INDEX TERMS Blockchain, peer-to-peer network, identity management system, self-sovereign identity, security.

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