Combining our GA-GAN quantum-resistant cryptography with QAES phonon classification, this paper presents an end-to-end secure communication protocol for DNA swarm nano-networks. The hybrid system achieves 96.8% true-positive bubble detection while encrypting data with GA-GAN-optimized keys, providing tap-proof channels for the Genesis Mission. Integration with QI-MARL energy balancing and DTN bundles ensures resilience in both terrestrial and cislunar environments.
Combining our GA-GAN quantum-resistant cryptography with QAES phonon classification, this paper presents an end-to-end secure communication protocol for DNA swarm nano-networks. The hybrid system achieves 96.8% true-positive bubble detection while encrypting data with GA-GAN-optimized keys, providing tap-proof channels for the Genesis Mission. Integration with QI-MARL energy balancing and DTN bundles ensures resilience in both terrestrial and cislunar environments.
This paper introduces “Quantum DNA Swarms,” a unified framework blending quantum-inspired swarm intelligence with DNA’s quantum properties for optimization and self-assembly. Building on Bloch Quantum Ant Colony Optimization (BQACO) [Li & Wang, 2012], we extend Bloch-sphere encoded agents to n-dimensional hypercube spaces via Pauli rotations. The framework integrates DTN bundles for resilient communication, SINUS-IT/QAES for noisy quantum-bio signals, BIONETS autonomic paradigms, experimental DNA-triggered active gels, QI-MARL for energy-aware coordination, GA-GAN for quantum-resistant encryption, and HCDSO with MD-LSTM for malicious detection and QoS-aware multicast routing in MANET environments. This work extends our 2025 Zenodo paper on quantum biological systems and opens new paths for bioinformatics, nano-computing, and space/molecular networks.
Extending our March 18, 2026 preprints (Zenodo Records 19093596, the “in Action” paper, and the new in-vitro protocol), this work scales QAES-stabilized phonon bubbles to 11D cosmic models (Carbó-Dorca simplices) and integrates them with Delay/Disruption Tolerant Networking (DTN) bundles for cislunar resilience. We demonstrate how DNA swarms maintain phonon-photon coherence across intermittent space links, enabling secure quantum communication and sensor networks for the Genesis Mission infrastructure. The framework combines our QI-MARL energy loop, QAES classification, and NASA DTN protocols to achieve 98% link success in simulated cislunar conditions.
As swarm robotics evolves into a paradigm-shifting approach for distributed autonomous systems, communication vulnerabilities pose risks in hostile environments. Conventional cryptography is limited by decentralized nature, energy constraints, and node density, while quantum computing threatens public-key encryption via Shor's algorithm. This chapter explores Quantum Key Distribution (QKD) and entanglement-based networking for information-theoretic security. We examine mobile quantum networks, highlighting drone-based relays and satellite links. Beyond security, quantum principles like superposition and entanglement can enhance swarm intelligence, task allocation, and coordination. Despite promising validations, hurdles remain: SWaP constraints, atmospheric interference, and mobility-induced decoherence. Through case studies in aerial, maritime, space, and disaster domains, we propose a quantum-native architecture integrating post-quantum cryptography, adaptive PAT systems, and hybrid trust models for mission-critical resilience.
Enhancing data security and privacy in distributed computing environments presents a key challenge in effectively deploying quantum protocols on edge devices with limited resources. The objective of this project is to enhance the security of edge devices by integrating secure quantum communication protocols using Quantum-Enhanced Generative Adversarial Networks (QE-GANs). To provide safe quantum communication integration for QE-GANs on edge devices, researchers can gather the necessary data through the data collection process from edge devices. For data pre-processing in speech recognition applications, Mel-frequency Cepstral Coefficients (MFCCs) are a popular choice. Measurement-Device-Independent Quantum Key Distribution (MDI-QKD) is a cutting-edge method that provides advanced security compared to conventional QKD for secure communication among edge devices. SMLA refers to secure multiparty logic and its utilization, a framework that enables secure communication between multiple parties while ensuring the confidentiality and integrity of the transmitted data. Qubit-masked messages (QMM) and Quantum Coded Modulated Discrete Permutation (QC-MDPC) are two sophisticated quantum communication methods for data encryption. ρ represents the quantum state density matrix; DFR refers to Device-Independent Quantum Secure Randomness Generation Protocol. MATLAB will be utilized to simulate and analyse the performance of QE-GANs) for integrating secure quantum communication protocols into edge devices. The findings show that the peak energy value of 23.7568 represents the dominant frequency component, which plays a key role in significantly influencing the signal. Integrating secure quantum communication protocols with edge devices via QE-GANs could revolutionize data privacy, enhancing real-time encryption, robust authentication, and decentralized trust, paving the way for next-gen secure IoT networks.
Artificial Intelligence (AI) combined with Bio-Quantum Computing is a revolutionary method of improving data security and encryption in virtual environments. Through the use of quantum mechanics and AI-optimized optimization, this combination strengthens cryptographic methods against future cyber threats. Current encryption algorithms like RSA and AES are vulnerable due to the advancement of Bio-Quantum Computing, which can decrypt conventional cryptographic algorithms. Additionally, traditional security systems are not able to adapt in real-time to advanced cyber-attacks. To meet these demands, the suggested framework combines AI with Quantum Key Distribution (AI -QKD). The QKD provides unbreakable key exchange cryptography using quantum properties, whereas AI optimizes encryption protocols in real time through threat analysis, providing heightened security resilience. This technique is used in virtual world transaction security, identity authentication, and secret communications. The AI-based mechanism flexibly adjusts encryption parameters in real time, preventing quantum attacks and increasing the integrity of the overall data. Findings reveal that the new approach enhances the robustness of encryption immensely, lowers risks of key compromise, and makes virtual interactions secure. The fusion of AI and QKD reflects high adaptability, making the encryption systems quantum-resistant and future-proof. The new approach achieves the data integrity by 98.70%, key compromise risks by 45.31%, adaptability by 97.63%.
This work explores quantum cryptography through frequency-bin encoding, leveraging photon frequencies for tap-proof entanglement distribution in reconfigurable networks. We integrate recent breakthroughs in Photonic Quantum Convolutional Neural Networks (PQCNNs) and transformer-based error decoding to enhance resilience in quantum processors. The paper demonstrates the first implementation of the BBM92 protocol using frequency bins, achieving adaptive multiplexing and multi-user scalability. Extending to cislunar resilience, Delay/Disruption Tolerant Networking (DTN) supports space-terrestrial V2X. These elements support resilient quantum networks aligned with the Genesis Mission’s emphasis on AI-accelerated quantum technologies and national laboratory infrastructure.