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Edge Intelligence (EI) integrates Edge Computing (EC) and ArtificialIntelligence (AI) to push the capabilities of AI to the network edge forreal-time, efficient and secure intelligent decision-making and computation.However, EI faces various challenges due to resource constraints, heterogeneousnetwork environments, and diverse service requirements of differentapplications, which together affect the trustworthiness of EI in the eyes ofstakeholders. This survey comprehensively summarizes the characteristics,architecture, technologies, and solutions of trustworthy EI. Specifically, wefirst emphasize the need for trustworthy EI in the context of the trend towardlarge models. We then provide an initial definition of trustworthy EI, exploreits key characteristics and give a multi-layered architecture for trustworthyEI. Then, we summarize several important issues that hinder the achievement oftrustworthy EI. Subsequently, we present enabling technologies for trustworthyEI systems and provide an in-depth literature review of the state-of-the-artsolutions for realizing the trustworthiness of EI. Finally, we discuss thecorresponding research challenges and open issues.

A Survey on Trustworthy Edge Intelligence: From Security and Reliability To Transparency and Sustainability