Leveraging Meta-Learning for Dynamic Anomaly Detection in Zero Trust Clouds

In the rapidly evolving landscape of cloud computing, ensuring the security of data and services remains an imperative challenge. The Zero Trust framework, advocating continuous verification and access control, presents a pivotal paradigm to mitigate risks. This research introduces a pioneering approach named “DeepMetaGuard” for addressing dynamic anomaly detection within Zero Trust cloud environments. By amalgamating the Model-Agnostic Meta-Learning (MAML) and Variational Autoencoders (VAEs)–a Deep Anomaly Detection model, DeepMetaGuard stands as a promising innovation. DeepMetaGuard harnesses the potential of meta-learning through MAML, which expedites the model's adaptation to diverse cloud scenarios, thereby enhancing its adaptability to anomalous behaviours. Simultaneously, its integration with VAEs equips the model to identify anomalies across various cloud environments by acquiring generalized knowledge while accommodating distinct traits. To assess DeepMetaGuard's efficacy, a comprehensive simulation analysis is conducted, comparing its performance against existing anomaly detection algorithms. The evaluation encompasses a spectrum of simulation metrics, including Area Under Curve–Precision Recall Metric (AUC-PR), Detection Time, Precision-Recall Gain Curves, and Matthews Correlation Coefficient (MCC). AUC-PR gauges precision-recall trade-offs, Detection Time measures response speed, Precision-Recall Gain Curves visualize incremental performance gains, and MCC balances overall model performance. In this pioneering study, DeepMetaGuard emerges as a proficient contender in dynamic anomaly detection within Zero Trust cloud environments. The amalgamation of meta-learning and deep anomaly detection techniques, as evidenced through the comprehensive evaluation, underscores its potential in redefining cloud security. By introducing DeepMetaGuard and substantiating its effectiveness against established benchmarks, this research contributes to the advancement of cybersecurity strategies in the realm of cloud systems.