Edge Computing for IoT: Novel Insights from a Comparative Analysis of Access Control Models
Tao Xue, Ying Zhang, Yanbin Wang, Wenbo Wang, Shuailou Li, Haibin Zhang
TL;DR
The paper systematically surveys access control for IoT edge computing through the data lifecycles of collection, storage, and usage, highlighting how traditional models (CapBAC, RBAC, ABAC, GBAC, CAAC, ReBAC, RAAC, TBAC) and cryptographic approaches (ABE) interact with blockchain-based enforcement. It analyzes end-edge-cloud architectures, identifies key requirements (resource constraints, latency, flexibility, scalability), and maps existing solutions to each lifecycle, including blockchain-enabled platforms and cross-lifecycle considerations. The authors extract lessons on performance trade-offs, privacy, and integration gaps, and propose future directions such as machine learning-driven policy generation, federated learning, hybrid schemes, and robust testbeds to validate complex, multi-model access control in practice. Overall, the work provides a comprehensive, lifecycle-spanning view that can guide researchers and practitioners in developing adaptive, secure, and scalable access-control techniques for IoT edge ecosystems.
Abstract
IoT edge computing positions computing resources closer to the data sources to reduce the latency, relieve the bandwidth pressure on the cloud, and enhance data security. Nevertheless, data security in IoT edge computing still faces critical threats (e.g., data breaches). Access control is fundamental for mitigating these threats. However, IoT edge computing introduces notable challenges for achieving resource-conserving, low-latency, flexible, and scalable access control. To review recent access control measures, we novelly organize them according to different data lifecycles--data collection, storage, and usage--and, meanwhile, review blockchain technology in this novel organization. In this way, we provide novel insights and envisage several potential research directions. This survey can help readers find gaps systematically and prompt the development of access control techniques in IoT edge computing under the intricacy of innovations in access control.