mlsanityData to 14 Oct 2026

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

arXiv 2310.17944 ↗First posted 27 Oct 2023cs.LGcited by 7

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Abstract (arXiv)

Edge Intelligence (EI) integrates Edge Computing (EC) and Artificial Intelligence (AI) to push the capabilities of AI to the network edge for real-time, efficient and secure intelligent decision-making and computation. However, EI faces various challenges due to resource constraints, heterogeneous network environments, and diverse service requirements of different applications, which together affect the trustworthiness of EI in the eyes of stakeholders. This survey comprehensively summarizes the characteristics, architecture, technologies, and solutions of trustworthy EI. Specifically, we first emphasize the need for trustworthy EI in the context of the trend toward large models. We then provide an initial definition of trustworthy EI, explore its key characteristics and give a multi-layered architecture for trustworthy EI. Then, we summarize several important issues that hinder the achievement of trustworthy EI. Subsequently, we present enabling technologies for trustworthy EI systems and provide an in-depth literature review of the state-of-the-art solutions for realizing the trustworthiness of EI. Finally, we discuss the corresponding research challenges and open issues.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 58 of its 163 references that are in the map. First posted on arXiv 27 Oct 2023.

Builds on

58 of 163 references.

References · 58

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38 more
  1. 2017A Survey on Homomorphic Encryption Schemes: Theory and Implementationcited by 156
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50 most cited of 58 All 58 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 5; 2026: 1.

7 papers.

  1. 2025Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Surveycited by 14
  2. 2024Towards Secure Intelligent O-RAN Architecture: Vulnerabilities, Threats and Promising Technical Solutions using LLMscited by 3
  3. 2025Neuro-Symbolic AI for Cybersecurity: State of the Art, Challenges, and Opportunitiescited by 2
  4. 2025Edge Artificial Intelligence: A Systematic Review of Evolution, Taxonomic Frameworks, and Future Horizonscited by 2
  5. 2025Benchmarking Vision Transformers and CNNs for Thermal Photovoltaic Fault Detection with Explainable AI Validationcited by 1
  6. 2025BcQLM: Efficient Vision-Language Understanding with Distilled Q-Gated Cross-Modal Fusioncited by 0
  7. 2026Sustainable Face Recognition on Low-Power Devices with VQ-VAE Embeddingscited by 0