Advances, Systems and Applications
Table 1 Admission control policy and Key Agreement Based on Anonymous Identity
From: Admission control policy and key agreement based on anonymous identity in cloud computing
Author | Proposed System | Algorithm | Year |
|---|---|---|---|
Nirmal Kumar et al. [30] | Deep Reinforcement Learning | multiagent deep RL (MADRL) | 2020 |
Qu et al. [31] | Reinforcement Learning | Policies for multi-agent Networked Systems | 2020 |
Spooner et al. [32] | Through Adversarial Reinforcement, Learning | Strong market-making is possible thanks to adversarial reinforcement learning. | 2020 |
Manzoor et al. [25] | Proxy broadcast repeat encryption | The blockchain-based platform for sharing Internet of Things data is secure and anonymous thanks to proxy re-encryption. | 2021 |
Patonico et al. [23] | Canetti and Krawczyk developed a risk assessment model. | Canetti-Krawczyk-resistant protocol for anonymous and identity-based fog computing | 2019 |
Chomping et al. [33] | Revocable identity-based broadcast proxy re-encryption for data sharing in clouds (RIBBPRE) | In RIB-BPRE, the agent has the re-encryption key and can revoke the authority of a delegation group. | 2019 |