A Systematic Review of Error-Correcting Code Embedding for Confidential Edge Storage: Methods, Architectures, and Future Research Directions

Abstract

The rapid proliferation of edge computing has introduced new challenges in ensuring data confidentiality, integrity, and availability under constrained computational and storage environments. Error-correcting code (ECC) embedding has emerged as a promising paradigm for secure and resilient edge storage by integrating redundancy, fault tolerance, and cryptographic obfuscation within a unified framework. This paper presents a systematic review of ECC embedding techniques tailored for confidential edge storage systems, emphasizing their interaction with modern cryptographic primitives, chaotic systems, and artificial intelligence-driven optimizations. The study analyzes recent advancements in code-based security architectures, including lattice-based constructions, Reed–Solomon and LDPC code embeddings, and hybrid chaotic-ECC encryption schemes. Key findings reveal that ECC embedding not only enhances robustness against data corruption and adversarial tampering but also contributes to lightweight encryption suitable for edge devices. Furthermore, the integration of generative AI models for adaptive key generation and anomaly detection is identified as a transformative direction. The contributions of this paper include a comprehensive synthesis of 30 recent studies, identification of research gaps in scalable and AI-assisted ECC frameworks, and the proposal of future research directions that align with secure software engineering and DevSecOps practices in distributed environments.