The modernization of distributed energy systems introduces complex cybersecurity challenges as grid infrastructures become increasingly digitized, decentralized, and web-connected. This paper presents a novel security architecture that integrates quantum key distribution (QKD) with semantic web technologies to provide end-to-end secure, scalable, and adaptive protection for distributed energy resource (DER) networks. The proposed framework features a modular system design, incorporating BB84-based QKD protocols for quantum-resilient key generation, a metadata-driven policy layer using OWL ontologies and SWRL reasoning, and a web interface for operator access and real-time monitoring. Extensive performance evaluation in a simulated multi-domain microgrid environment demonstrates that the system achieves an average key generation rate of 2.3 kbps with quantum bit error rate (QBER) maintained below 5.2% across 40 km optical links. Session establishment latency averaged 435 ms, 29.8% lower than a traditional TLS/PKI baseline, while semantic access validation achieved 100% accuracy in 42 adversarial test cases. These cases were evaluated using automated semantic validation scripts simulating spoofed roles, malformed sessions, and unauthorized requests. The system sustained encrypted throughput of 110 messages per second per node and maintained service continuity under quantum noise and cross-domain attack simulations. Usability trials with six engineers yielded a system usability scale (SUS) score of 88.3, and the average DER onboarding time was reduced from 10.1 to 5.5 minutes. These findings affirm that QKD-enhanced, semantically governed web architectures can provide strong cryptographic guarantees while supporting dynamic policy enforcement and intuitive user workflows. The proposed solution demonstrates a viable path for deploying future-proof security mechanisms in next-generation smart grid environments.
The modernization of distributed energy systems introduces complex cybersecurity challenges as grid infrastructures become increasingly digitized, decentralized, and web-connected. This paper presents a novel security architecture that integrates quantum key distribution (QKD) with semantic web technologies to provide end-to-end secure, scalable, and adaptive protection for distributed energy resource (DER) networks. The proposed framework features a modular system design, incorporating BB84-based QKD protocols for quantum-resilient key generation, a metadata-driven policy layer using OWL ontologies and SWRL reasoning, and a web interface for operator access and real-time monitoring. Extensive performance evaluation in a simulated multi-domain microgrid environment demonstrates that the system achieves an average key generation rate of 2.3 kbps with quantum bit error rate (QBER) maintained below 5.2% across 40 km optical links. Session establishment latency averaged 435 ms, 29.8% lower than a traditional TLS/PKI baseline, while semantic access validation achieved 100% accuracy in 42 adversarial test cases. These cases were evaluated using automated semantic validation scripts simulating spoofed roles, malformed sessions, and unauthorized requests. The system sustained encrypted throughput of 110 messages per second per node and maintained service continuity under quantum noise and cross-domain attack simulations. Usability trials with six engineers yielded a system usability scale (SUS) score of 88.3, and the average DER onboarding time was reduced from 10.1 to 5.5 minutes. These findings affirm that QKD-enhanced, semantically governed web architectures can provide strong cryptographic guarantees while supporting dynamic policy enforcement and intuitive user workflows. The proposed solution demonstrates a viable path for deploying future-proof security mechanisms in next-generation smart grid environments.
ABSTRACT The increasing complexity of smart grid IoT ecosystems demands security architectures capable of resisting quantum‐era threats, protecting data privacy, and scaling across large distributed infrastructures. This study introduces a novel hybrid security framework that integrates quantum cryptography, deep learning–based intrusion detection, and federated learning into a unified, high‐assurance design tailored for next‐generation smart grid environments. The architecture employs quantum key distribution (QKD) for secure key generation, an adaptive deep feature obfuscation layer to mitigate adversarial manipulation, and a privacy‐preserving federated learning pipeline that eliminates centralized data exposure. Simulation‐based evaluations demonstrate substantial performance gains, achieving a low quantum bit error rate (1.8%), high key‐generation throughput (4900 keys/s), low latency (18 ms), and intrusion detection accuracy of 98.7%, consistently outperforming conventional cryptographic and machine learning baselines. The framework further exhibits enhanced resilience against quantum‐based and adversarial attacks, with efficient performance maintained even under increasing network density. While real‐world deployment will require hardware‐in‐the‐loop validation and optimization for heterogeneous traffic conditions, the results indicate strong potential for securing future smart grid IoT infrastructures and supporting sustainable smart city applications.
The energy and power industry faces increasing data security challenges amidst its digital transformation. Databases, as the foundation of digital infrastructure, require advanced encryption techniques to safeguard sensitive information. This paper proposes a novel encryption framework, QKD-ABE, that integrates Quantum Key Distribution (QKD) with Attribute-Based Encryption (ABE) to enhance the confidentiality, integrity, and access control of power system data. QKD enables unconditional security in key distribution by leveraging quantum mechanics, effectively preventing key interception and tampering. ABE provides fine-grained access control by enforcing encryption policies based on user attributes, ensuring that only authorized individuals can access private data. The proposed scheme also demonstrates strong resistance to common security threats, including man-in-the-middle and eavesdropping attacks, through quantum measurement disturbance and Quantum Bit Error Rate (QBerr) verification. Experimental results and theoretical analysis indicate that QKD-ABE offers a secure, efficient, and scalable solution for protecting sensitive data in modern smart grid environments.
The development and evolution of the smart grid into complex, cyber-physical energy systems make it essential to secure?communication among the distributed components. The rise of quantum computing has made it even more pressing to develop protocols that?are secure outside the limitations of classical cryptosystems. In this paper, it proposes a quantum-assisting secure communication scheme (QASCP) to?boost the security and energy for smart grid communication systems. The proposed protocol combines quantum key distribution with lightweight entropy-based mutual authentication and dynamic session management. It is designed to defend grid assets such as control centers, smart meters, and distribute energy?resources from sophisticated adversarial models, including quantum-capable threats. The approach consists of system level simulation utilizing a?co-simulation framework customized for quantum smart grid communication. The performance of this scheme was compared?against classical and PQ lattice-based schemes in terms of the authentication latency, energy consumption, entropy preservation, and scalability to handle the load and delay effects, under the assumptions of different loading and delay scenarios. Simulation results show that QASCP is able to reduce the energy consumption and authenticity latency, simultaneously it keeps the high throughput and leaves strong entropy?under attack scenarios. The protocol is also shown to?remain robust with varying quantum bit error rates as well as having a smaller memory footprint on popular network topologies. The results provide evidence for the practical integration of?quantum-secure communication in smart grid architectures. By addressing security and performance simultaneously, the protocol?provides a path to future-proof energy networks which can support dependable operations in a quantum-enhanced environment. This could be future enhance for energy efficiency.
The increasing interconnection of smart-grid operational technology, industrial-edge services, and utility information systems creates a critical need for resilient and continuously monitored industrial cyber-physical communication. Although quantum key distribution (QKD) can strengthen session-key establishment for advanced metering infrastructure, distributed energy resources, substation automation, supervisory control, and utility-core services, practical QKD deployments remain vulnerable to implementation-level side-channel attacks that can compromise the cryptographic protection layer without directly targeting conventional network packets. This paper presents a QKD-secured industrial smart-grid cyber-physical system framework for simulating and detecting adaptive side-channel attacks. The proposed 36-node industrial communication architecture integrates AMI devices, DER controllers, PMU and substation automation components, industrial-edge gateways, QKD modules, key-management services, SCADA and utility-core servers, security-operation-center components, and adversarial access points. A 100,000-record cyber-quantum dataset is generated across 12 operating conditions comprising normal communication and 11 adaptive QKD side-channel attacks: detector blinding, time shift, wavelength switching, Trojan-horse probing, photon-number splitting, decoy-state spoofing, RNG bias, calibration manipulation, local-oscillator manipulation, synchronization spoofing, and combined adaptive quantum hacking. Each scenario introduces coupled primary and secondary perturbations across optical, detector, timing, synchronization, randomness, calibration, photon-statistical, leakage, key-generation, encryption, and industrial-network-performance features. To support intelligent industrial security monitoring, the proposed Quantum-aware Mamba–Kolmogorov–Arnold Network (Q-MambaKAN) organizes device, network, QKD, side-channel, encryption, and risk evidence into an ordered cyber-quantum representation processed through selective state-space learning, side-channel attention, nonlinear KAN mapping, adaptive fusion, and multi-task prediction heads. Results show that the QBER increases from 0.071 during normal operation to 0.426 under combined adaptive quantum hacking, while encryption success decreases from 98.1% to 0%. Q-MambaKAN achieves a 99.48% binary detection accuracy, a 99.70% binary F1-score, a 97.60% multiclass macro-F1, and a risk RMSE of 0.021.
Quantum Key Distribution (QKD) represents a paradigm shift in cryptographic security, offering information-theoretic confidentiality based on fundamental principles of quantum mechanics rather than computational hardness assumptions. The emergence of advanced quantum processors with ever-increasing qubit counts has accelerated the timeline for cryptographically-relevant quantum computers, necessitating immediate migration to quantum-safe communication protocols. This paper introduces a comprehensive QKD-based network integrity mechanism implemented as a Flask-based web chatting application that provides end-to-end security with real-time attack detection and automated mitigation. The system integrates a complete BB84 protocol simulation with polarized photon transmission modeling, incorporating realistic quantum channel parameters including attenuation (0.2 dB/km), dark count probability (10⁻⁶), and detector efficiency (30%). The architecture comprises four integrated modules: Quantum Key Distribution Engine implementing the full BB84 protocol stack with adaptive basis selection and error reconciliation; Secure Chat Interface supporting multi-user rooms, private messaging, and file sharing with one-time pad encryption using quantum-generated keys refreshed at optimal intervals; Network Integrity Monitor employing statistical analysis and machine learning techniques to detect eavesdropping attempts through quantum bit error rate (QBER) analysis, timing anomalies, and photon statistics; Automated Mitigation System that quarantines detected attackers through session termination, IP blacklisting, key revocation, and emergency key regeneration. Experimental evaluation demonstrates detection rates of 99.7% for intercept-resend attacks at 24.8% QBER, 98.2% for photon number splitting attacks at 15.3% QBER, and 99.1% for man-in-the-middle attacks at 18.7% QBER. The system achieves key generation rates of 1.82 kbps over 10 km simulated fiber, with 1.8-second quarantine response time meeting stringent incident response requirements. Scalability testing confirms support for 5,000+ concurrent users with 320 ms response time, making the solution suitable for production deployment. This work represents the first production-ready integration of quantum key distribution with a complete web chat application featuring automated attack detection and mitigation, bridging the gap between theoretical quantum cryptography and practical secure communication tools.
Quantum Key Distribution (QKD) represents a paradigm shift in cryptographic security, offering information-theoretic confidentiality based on fundamental principles of quantum mechanics rather than computational hardness assumptions. The emergence of advanced quantum processors with ever-increasing qubit counts has accelerated the timeline for cryptographically-relevant quantum computers, necessitating immediate migration to quantum-safe communication protocols. This paper introduces a comprehensive QKD-based network integrity mechanism implemented as a Flask-based web chatting application that provides end-to-end security with real-time attack detection and automated mitigation. The system integrates a complete BB84 protocol simulation with polarized photon transmission modeling, incorporating realistic quantum channel parameters including attenuation (0.2 dB/km), dark count probability (10⁻⁶), and detector efficiency (30%). The architecture comprises four integrated modules: Quantum Key Distribution Engine implementing the full BB84 protocol stack with adaptive basis selection and error reconciliation; Secure Chat Interface supporting multi-user rooms, private messaging, and file sharing with one-time pad encryption using quantum-generated keys refreshed at optimal intervals; Network Integrity Monitor employing statistical analysis and machine learning techniques to detect eavesdropping attempts through quantum bit error rate (QBER) analysis, timing anomalies, and photon statistics; Automated Mitigation System that quarantines detected attackers through session termination, IP blacklisting, key revocation, and emergency key regeneration. Experimental evaluation demonstrates detection rates of 99.7% for intercept-resend attacks at 24.8% QBER, 98.2% for photon number splitting attacks at 15.3% QBER, and 99.1% for man-in-the-middle attacks at 18.7% QBER. The system achieves key generation rates of 1.82 kbps over 10 km simulated fiber, with 1.8-second quarantine response time meeting stringent incident response requirements. Scalability testing confirms support for 5,000+ concurrent users with 320 ms response time, making the solution suitable for production deployment. This work represents the first production-ready integration of quantum key distribution with a complete web chat application featuring automated attack detection and mitigation, bridging the gap between theoretical quantum cryptography and practical secure communication tools.