… study concerning FL’s security and privacy aspects that can help bridge the gap between the
current state of federated … a detailed review of security and privacy concerns that need to be …

… Federated learning … security and privacy-preserving learning environment. It is thus highly
necessary to comprehensively identify and classify potential threats to utilize FL under security …

… We survey privacy and security attacks to federated learning and … Security attacks and
countermeasures In this section, we discuss the security implications of federated learning. From …

… (1) Privacy protection: Since federated learning is proposed to solve the … of privacy data
protection in machine learning, we must ensure that the training model in federated learning …

… in our search, ie, adversarial federated learning, poisoning federated learning, … federated
learning, attack federated learning, threat federated learning, and defense federated learning. …

… comprehensive study concerning various privacy and security issues related to federated
learning. … Findings from our study confirm that the current major security threats are poisoning, …

… federation and motivation of federation. The categorization can help the design of federated
learning … By systematically summarizing the existing federated learning systems, we present …

… ABSTRACT This paper provides a comprehensive study of Federated Learning (FL) with an
… ‘‘A novel approach to machine learning application to protection privacy data in healthcare: …

… of data silos and popular privacy awareness, the traditional centralized approach of training
artificial intelligence (AI) models is facing strong challenges. Federated learning (FL) has …

… long-standing privacy risks to personal data leakage, misuse, and abuse. Federated learning
(FL… that facilitates distributed collaborative learning without disclosing original training data. …