Endogenous Security of $FQ_{n}$ Networks: Adaptive System-Level Fault Self-Diagnosis

Endogenous security has the ability to discover, eliminate, and solve internal security problems and hidden dangers within the network, and is a superior technology to ensure future network security. The
$t/k$
-diagnosis strategy, as a strong and adaptive self-diagnosis strategy, is an important part for ensuring endogenous security. Moreover, the folded hypercube (
$FQ_{n}$
) as a data transmission network (e.g., optical network) topology offers new potential for the construction of large-scale, high data throughput, and low-latency systems, such as computing network, human-cyber-physical systems, and smart grid. However, there are few studies on endogenous security based on
$FQ_{n}$
networks. Therefore, this article designs an adaptive system-level fault self-diagnosis strategy, namely Fast t/k-Diagnosis Under Maeng-Malek Model (Ftk-DIAG-MM
^*
) to diagnosis the faulty vertices in
$FQ_{n}$
network under the Maeng-Malek model (MM* mod). Then, we provide a proof of the algorithm correctness theoretically by the fault tolerance of
$FQ_{n}$
network. It is derived by theoretical derivation that the
$t/k$
-diagnosability inherent to the
$FQ_{n}$
network is
$(n+1)(k+1)-k(k+3)/2$
. The simulation experiments demonstrate that the designed Ftk-DIAG-MM* strategy can correctly diagnose all vertices within the range allowed by the diagnosability, and still has a great performance when it exceeds the range allowed by the diagnosability. It greatly enhances the fault diagnosis capability of
$FQ_{n}$
network in the circumstance of misdiagnosing a few vertices, which provides an important theoretical basis for the reliability and endogenous security of
$FQ_{n}$
networks.