Authors: Shrihari.G, Abilash.R
Abstract: Modern cloud infrastructures host large numbers of distributed services and microservices, where failures and attacks can propagate rapidly across virtual machines, containers, and orchestration layers. In this setting, static, signature-driven defenses are insufficient to maintain availability and resilience. Inspired by the biological immune system (BIS), this paper presents a self-healing cloud infrastructure framework that applies second-generation Digital Immune System (DIS) principles to detect, contain, and recover from process-level anomalies in real time. The approach treats cloud nodes and services as components of a larger artificial organism, embedding immune-like agents throughout the stack rather than relying solely on perimeter defense. At the core of the framework is a biologically plausible, multi-layered cellular signalling architecture for process anomaly detection. Building on Matzinger’s Danger Theory, the system moves beyond simple self/non-self discrimination by combining “danger signals” such as abnormal syscall patterns, privilege escalation attempts, and volatile resource usage with “safe signals” derived from stable workload and performance baselines. Specialized artificial cell populations—Dendritic Cells (aDCs), T-Helper Cells (T_H), and B-Cells—are instantiated as distributed agents within a cloud-aware middleware. aDCs aggregate local evidence on each node, T_H cells perform distributed consensus across nodes and services, and B-Cells maintain memory detectors that rapidly recognize previously observed attack strategies. These immune agents communicate over a virtual cytokine bus, enabling spatial-temporal correlation of signals across containers, virtual machines, and availability zones. When coordinated danger levels exceed adaptive thresholds, the framework triggers self-healing actions such as throttling or isolating compromised containers, rolling back affected service instances, or re-provisioning clean replicas through the underlying orchestration platform. Evaluation on syscall-level datasets and realistic exploit scenarios indicates that the proposed DIS-based controller can distinguish normal from attack behaviour with high accuracy while imposing minimal overhead, and that its coordinated responses significantly reduce both time-to-detection and time-to-recovery compared to baseline policies. The work demonstrates that biologically inspired, multi-agent immunity can provide a practical foundation for self-healing cloud infrastructure capable of adapting alongside evolving threats.
