Academic literature on the topic 'Quantum-Resistant Cryptography (QRC)'

The NISQ era is a transitional phase in the development of quantum computing with a limited number of qubits and high noise levels. In response to the limitations, specialized algorithms have been developed, such as the variational quantum eigenvalue algorithm (VQE) for modeling molecular structures, and QAOA for solving combinatorial optimization problems. To reduce the impact of noise on the calculations, effective strategies are used: randomized compilation (RC) and zero-noise extrapolation (ZNE). Hybrid quantum-classical approaches are also being developed that combine quantum generation with classical optimization and processing methods. Potential areas of application of NISQ technologies include the optimization of logistics problems, financial modeling, and supply chain optimization. In cryptography, NISQ devices stimulate the development of quantum-resistant encryption algorithms. The main challenges remain the limited scalability of systems and the problem of noise in quantum computing. The search for new architectures, including topological qubits and "glass" chips for a more stable environment, continues. An important trend is the gradual transition to the era of fully fault-tolerant quantum computers (FTQC), expected in the period 2025-2029. Unlike NISQ, which focuses on noise reduction methods, FTQC implements full quantum error correction (QEC). Quantum computing has transformed from an academic discipline into a field with a clear commercial strategy. Despite current limitations, existing achievements open up real opportunities for the applied use of quantum computing in cryptography. The analysis of mathematical criteria of different eras of quantum computing development has implications for solving cryptanalytic problems, transforming the understanding of the time frames and methodological approaches to overcoming cryptographic protection of classical cryptosystems.

The Bit Commitment (BC) is an important basic agreement in cryptography . The concept was first proposed by the winner of the Turing Award in 1995 ManuelBlum. Bit commitment scheme can be used to build up zero knowledge proof, verified secret sharing, throwing coins etc agreement.Simultaneously and Oblivious Transfer together constitute the basis of secure multi-party computations. Both of them are hotspots in the field of information security. We investigated unconditional secure Quantum Bit Commitment (QBC) existence. And we constructed a new bit commitment model – double prover bit commitment. The Quantum Bit Commitment Protocol can be resistant to errors caused by noise.

Quantum Machine Learning (QML) has advanced significantly thanks to the combination of Quantum Computing (QC) with Artificial Intelligence (AI), hence releasing computational benefits over conventional methods. This synergy does, however, also bring fresh security flaws like adversarial attacks, quantum noise manipulation, and cryptographic weaknesses. This work offers a thorough investigation of QML security along with an examination of its special vulnerabilities resulting from hardware-induced faults, quantum variational circuits, and quantum data encoding. We methodically investigate adversarial attack techniques using the probabilistic character of quantum states including side-channel assaults, quantum noise injection, and algorithmic perturbations. We also assess innovative defensive strategies such differential privacy, quantum adversarial training, quantum error correction (QEC), cryptographic techniques include Quantum Homomorphic Encryption (QHE), We offer a hybrid AI-driven method for protecting QML models against developing threats by linking artificial intelligence and quantum security frameworks. This work emphasizes the importance of developing quantum-safe AI systems and consistent adversarial robustness standards. The results help to advance AI-enhanced quantum security, thereby guaranteeing the future of QML applications is efficient, strong, and resistant to adversarial attack.