Age of Trust (AoT): A Continuous Verification Framework for Wireless Networks

TL;DR

The paper introduces Age of Trust (AoT), a time-evolving metric that captures trust decay between verifications and defines an average AoT $\Delta$ to quantify long-term trust levels. It formulates a bi-objective optimization between $\Delta$ and throughput for both single-link and multi-access wireless settings, proposing a periodic verification scheme and a Q-learning-based scheme to adapt verification, with an additional trust-enhanced frame-slotted ALOHA for multiple random access. The methods are analyzed under constant, random with known average, and random with known instantaneous service rates, and validated via simulations showing that AoT can be balanced with throughput to achieve practical zero-trust architectures. The results demonstrate that AoT-aware designs can offer reliable security while preserving transmission efficiency, making AoT a versatile tool for next-generation wireless security provisioning.

Abstract

Zero Trust is a new security vision for 6G networks that emphasises the philosophy of never trust and always verify. However, there is a fundamental trade-off between the wireless transmission efficiency and the trust level, which is reflected by the verification interval and its adaptation strategy. More importantly, the mathematical framework to characterise the trust level of the adaptive verification strategy is still missing. Inspired by this vision, we propose a concept called age of trust (AoT) to capture the characteristics of the trust level degrading over time, with the definition of the time elapsed since the last verification of the target user's trust plus the initial age, which depends on the trust level evaluated at that verification. The higher the trust level, the lower the initial age. To evaluate the trust level in the long term, the average AoT is used. We then investigate how to find a compromise between average AoT and wireless transmission efficiency with limited resources. In particular, we address the bi-objective optimization (BOO) problem between average AoT and throughput over a single link with arbitrary service process, where the identity of the receiver is constantly verified, and we devise a periodic verification scheme and a Q-learning-based scheme for constant process and random process, respectively. We also tackle the BOO problem in a multiple random access scenario, where a trust-enhanced frame-slotted ALOHA is designed. Finally, the numerical results show that our proposals can achieve a fair compromise between trust level and wireless transmission efficiency, and thus have a wide application prospect in various zero-trust architectures.

Figures (14)

• Figure 1: The AoT process, where the initial age $\delta_i$ depends on the evaluated trust value at the $i$th verification. The higher the evaluated trust level is, the smaller the initial age will be.
• Figure 2: Continuous trust verification for the case of constant service process ($\mu(t) = 7$ and $\alpha = 1$).
• Figure 3: Continuous trust verification for the case of random service process ($\alpha = 1$).
• Figure 4: Continuous trust verification with using enhanced frame slotted ALOHA.
• Figure 5: AoT process of each sensor.

Theorems & Definitions (2)

• Theorem 1
• Theorem 2