The emergence of microgrids and the increasing adoption of Distributed Generation Systems (DGS) have created an opportunity to replace traditional fossil fuels with renewable resources. Such a shift poses security and power quality challenges that must be addressed by academics and industrial research paradigms. Unintentional islanding is an important security concern, as it can result in power quality degradation, electrical hazards, and equipment damage. To address this problem and find efficient solutions, many anti-islanding techniques to detect and eliminate the phenomenon can be found in the specialized literature. These solutions can be classified as passive, active, remote, hybrid, or based on machine learning and signal processing techniques. In this context, this paper provides a comprehensive review of existing antiislanding methods, highlighting their importance in preventing dangerous situations. The review includes a detailed analysis of advantages and limitations found for each method, as well as its suitability for practical applications. The goal is to provide a valuable resource for researchers and practitioners in the field of distributed power systems, enabling them to choose the most appropriate anti-islanding method for their specific needs. Overall, this paper aims to address the challenges posed by unintentional islanding and promote the adoption of renewable energy resources for a more sustainable future.