Applied Artificial Intelligence (Dec 2024)
Privacy Issues, Attacks, Countermeasures and Open Problems in Federated Learning: A Survey
Abstract
Aim This study presents a cutting-edge survey on privacy issues, security attacks, countermeasures and open problems in FL.Methodology The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach was used to determine the research domain, establish a search query, and analyze all retrieved articles from the selected scientific databases (i.e. ACM, ArXiv, Google Scholar, IEEE, Scopus, ScienceDirect, and Springer) to meet eligibility criteria and select relevant articles. A total of 1783 articles were retrieved, and 112 articles were deemed eligible for the study.Result This study identified five categories and eleven types of attacks, as well as six types of security attack countermeasures in FL. The results show that privacy and heterogeneity issues are the most common open problems in FL, comprising 38% of the selected articles, while data poisoning emerges as the most common attack, constituting 25% of all attacks identified in the study. The results also show that differential privacy can be used to combat six types of attacks, while anomaly detection can be utilized to combat four types of attacks.Conclusion This study reveals that If researchers and industry experts fail to solve the additional security concerns that occur from transferring training to personal devices and private enterprises, FL adoption may come to a standstill.