The Smart Grid concept evolved from the idea of intelligent and secure management of electrical grid infrastructure components and their communication through sustainable integration with the state-of-the-art technologies. This research focuses on emerging quantum computing-assisted security and its application in the Smart Grid. The robustness of electrical grid is increasing every day through advancements in grid infrastructure management which include outage control, relay protection, reliable distribution, renewable energy resource integration, and energy trading. Quantum Computing emerges as a formidable solution for application in the smart grid due to its processing capability and scale. Its application and scope are evolving every day with the recent developments in Quantum Chips which could pave the way for emerging Quantum-Chain-of-Things (QCoT). This research focuses on providing robust security in smart grids through Quantum Physical Unclonable Functions (QPUF) primitive, a quantum-hardware assisted security approach driven by micro manufacturing quantum process variations for generating a quantum digital fingerprint driven by quantum mechanics principles. The QPUF experimental evaluation in this research was performed to uniquely fingerprint various electrical grid entities providing a sustainable and secure flow of communication. Experimental evaluation shows a robust and reliable extraction of quantum digital fingerprints from noisy IBM quantum systems. The evaluation shows an impressive 86% keys achieving 100% reliability.

Sustainable advancement is being made to improve the efficiency of the generation, transmission, and distribution of renewable energy resources, as well as managing them to ensure the reliable operation of the smart grid. Supervisory control and data acquisition (SCADA) enables sustainable management of grid communication flow through its real-time data sensing, processing, and actuation capabilities at various levels in the energy distribution framework. The security vulnerabilities associated with the SCADA-enabled grid infrastructure and management could jeopardize the smart grid operations. This work explores the potential of Quantum Physical Unclonable Functions (QPUF) for the security and reliability of the smart grid’s energy transmission and distribution framework. Quantum computing has emerged as a formidable security solution for high-performance computing applications through its probabilistic nature of information processing. This work has a quantum hardware-assisted security mechanism based on intrinsic properties of quantum hardware driven by quantum mechanics to provide tamper-proof security for quantum computing-driven smart grid infrastructure. This work introduces a novel QPUF architecture using quantum logic gates based on quantum decoherence, entanglement, and superposition. This generates a unique bitstream for each quantum device as a fingerprint. The proposed QPUF design is evaluated on IBM and Google quantum systems and simulators. The deployment on IBM quantum (ibmq_qasm_simulator) and Google Cirq simulators has achieved 100% reliability with an average Hamming distance of 50.07%, 51% randomness.

Deepfake has emerged as a threat to individual’s privacy and identity. It uses advanced deep learning algorithms to synthesize visual, text, and audio from multimedia content in a realistic way. The advancement of Deepfake techniques is posing a question on the integrity of the digital content on social media. This work presents a novel hardware assisted Deepfake mitigation approach through the device and content integrity verification. In this work, the potential of hardware security primitive Physical Unclonable Functions (PUF) for mitigation of visual Deepfakes has been explored. The proposed framework presents a novel PUF-based image attestation technique that uses human facial features to create a unique pseudo-identity. The proposed architecture maps facial key point coordinates of each person in an image to PUF and creates a unique PUF generated key thereby having a unique pseudo identity for each image. Experimental evaluation uses Dlib facial detection model for facial attribute extraction and uses Arbiter PUF for image attestation.

The increasing threat to individual privacy and personalized digital content on social media posed by Deepfakes has highlighted the importance for a secure and reliable multimedia content integrity mechanism. In this paper a novel Blockchain driven hardware secure video attestation scheme, BlockShield is proposed for Deepfake mitigation. The proposed system includes a novel approach that ensures digital content traceability and privacy using Blockchain smart contracts and TPM's digital signature mechanism. The proposed work explores the scope of hardware-assisted security for Deepfake mitigation through a hardware TPM working together with Blockchain for enhanced digital media protection and sharing. The proposed work is experimentally validated and presented which validates the scope of hardware-assisted and blockchain integrated Deepfake mitigation framework.

This work presents a sustainable cybersecurity solution using Physical Unclonable Functions (PUF), Trusted Platform Module (TPM), and Tangle Distributed Ledger Technology (DLT) for sustainable device and data security. Security-by-Design (SbD) or Hardware- Assisted Security (HAS) solutions have gained much prominence due to the requirement of tamper-proof storage for hardwareassisted cryptography solutions. Designing complex security mechanisms can impact their efficiency as IoT applications are more decentralized. In the proposed architecture, we presented a novel TPM-enabled PUF-based security mechanism with effective integration of PUF with TPM. The proposed mechanism is based on the process of sealing the PUF key in the TPM, which cannot be accessed outside the TPM and can only be unsealed by the TPM itself. A specified NV-index is assigned to each IoT node for sealing the PUF key to TPM using the Media Access Control (MAC) address. Access to the TPM's Non-Volatile Random Access Memory (NVRAM) is defined by the TPM's Enhanced Authorization policies as specified by the Trust Computing Group (TCG). The proposed architecture uses Tangle for sustainable data security and storage in decentralized IoT systems through a Masked Authentication Messaging (MAM) scheme for efficient and secure access control to Tangle. We validated the proposed approach through experimental analysis and implementation, which substantiates the potential of the presented PUFchain 4.0 for decentralized IoT-driven security solutions.