Abstract
By 2040, malware targeting small devices will exhibit self-coordinating, polymorphic, and physically embedded behaviors, exploiting cross-modal sensor surfaces, firmware-level persistence, and side-channel emissions. Existing multimodal agent-based malware defense frameworks remain constrained by classical message passing, centralized model dependencies, and static trust assumptions.
This paper introduces Quantum-Mycelial Multimodal Agent Defense (MMAD), a fundamentally new defense paradigm for small devices. MMAD replaces explicit coordination with implicit state correlation, employs self-organizing trust hypergraphs, and leverages high-dimensional multimodal inference to detect and neutralize emergent malware behaviors under extreme resource constraints.
I present the theoretical foundations, agent architecture, learning dynamics, security guarantees, and a realistic commercialization pathway extending to 2050–2080, demonstrating how MMAD could evolve into deployable multimodal malware defense platforms.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Manuel-Devadoss, Johny, "Mycelial Multimodal Agent Defense (MMAD) - Ultra-Granular, Post-Signature Malware Defense for Resource-Constrained Devices", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/9992