Quantum secured blockchain framework for enhancing post quantum data security.

The Internet of Things (IoT) now underpins critical systems like healthcare monitors, smart home, smart grids, automotive V2V & V2X networks, and industrial controls but it still relies on classical cryptography, whose security assumptions are vulnerable to quantum computers. A large quantum computer could run Shor’s algorithm to break RSA/ECC and use Grover’s algorithm to accelerate brute-forcing of symmetric keys, undermining the confidentiality and authentication of data in these IoT applications. Researchers have proposed quantum cryptographic solutions. Quantum key distribution (QKD) and quantum random number generators (QRNGs) exploit quantum mechanics to detect eavesdropping and deliver provably secure key material. For example, chip-scale QRNGs can be embedded in IoT sensors to generate true random keys, boosting resistance to brute-force attacks. These quantum techniques provide information-theoretic secrecy, for instance, QKD-generated keys have been used to authenticate smart-grid SCADA. However, most IoT devices are resource-constrained, making direct deployment of conventional QKD hardware challenging. Post-quantum cryptography (PQC) complements quantum methods by providing algorithms such as lattice-based, hash-based that resist quantum attacks on existing hardware. Standardized PQC can be deployed via software updates on legacy IoT nodes, enabling scalable and quantum-safe security within current constraints. Researchers are exploring lightweight PQC for connected cars and e-health sensors. Hybrid approaches combining QKD/QRNG with PQC offer a layered defense. Since QKD protocols are regarded as ‘future-proof’ and PQC standards mature, their combined use will be essential for robust, quantum-safe IoT security. Miniaturizing quantum components such as integrated QKD/QRNG modules and optimizing lightweight PQC schemes for low-power IoT devices are future research directions to secure IoT networks.

Modern cryptography pushed forward the need of having provable security. Whereas ancient cryptography was only relying on heuristic assumptions and the secrecy of the designs, nowadays researchers try to make the security of schemes to rely on mathematical problems which are believed hard to solve. When doing these proofs, the capabilities of potential adversaries are modeled formally. For instance, the black-box model assumes that an adversary does not learn anything from the inner-state of a construction. While this assumption makes sense in some practical scenarios, it was shown that one can sometimes learn some information by other means, e.g., by timing how long the computation take. In this thesis, we focus on two different areas of cryptography. In both parts, we take first a theoretical point of view to obtain a result. We try then to adapt our results so that they are easily usable for implementers and for researchers working in practical cryptography. In the first part of this thesis, we take a look at post-quantum cryptography, i.e., at cryptographic primitives that are believed secure even in the case (reasonably big) quantum computers are built. We introduce HELEN, a new public-key cryptosystem based on the hardness of the learning from parity with noise problem (LPN). To make our results more concrete, we suggest some practical instances which make the system easily implementable. As stated above, the design of cryptographic primitives usually relies on some well-studied hard problems. However, to suggest concrete parameters for these primitives, one needs to know the precise complexity of algorithms solving the underlying hard problem. In this thesis, we focus on two recent hard-problems that became very popular in post-quantum cryptography: the learning with error (LWE) and the learning with rounding problem (LWR). We introduce a new algorithm that solves both problems and provide a careful complexity analysis so that these problems can be used to construct practical cryptographic primitives. In the second part, we look at leakage-resilient cryptography which studies adversaries able to get some side-channel information from a cryptographic primitive. In the past, two main disjoint models were considered. The first one, the threshold probing model, assumes that the adversary can put a limited number of probes in a circuit. He then learns all the values going through these probes. This model was used mostly by theoreticians as it allows very elegant and convenient proofs. The second model, the noisy-leakage model, assumes that every component of the circuit leaks but that the observed signal is noisy. Typically, some Gaussian noise is added to it. According to experiments, this model depicts closely the real behaviour of circuits. Hence, this model is cherished by the practical cryptographic community. In this thesis, we show that making a proof in the first model implies a proof in the second model which unifies the two models and reconciles both communities. We then look at this result with a more practical point-of-view. We show how it can help in the process of evaluating the security of a chip based solely on the more standard mutual information metric.

A roadmap from classical cryptography to post-quantum resistant cryptography for 5G-enabled IoT: Challenges, opportunities and solutions

The rapid expansion of the Internet of Things (IoT) has introduced unprecedented cybersecurity challenges, as traditional cryptographic methods struggle to provide both efficiency and quantum resistance in resource-constrained environments. This research introduces Adaptive Quantum Cryptography (AQC), a novel security framework that integrates Quantum Key Distribution (QKD), Post-Quantum Cryptography (PQC), Quantum Random Number Generators (QRNGs), and AI-driven dynamic adaptation to safeguard IoT networks against evolving cyber threats. Unlike classical encryption techniques such as RSA and ECC, which are vulnerable to quantum attacks, AQC leverages quantum mechanical principles—such as superposition, entanglement, and the no-cloning theorem—to ensure provably secure key exchange and data encryption. The proposed AQC system dynamically adjusts cryptographic protocols based on real-time network conditions, computational resources, and threat intelligence, optimizing security without imposing excessive overhead. Experimental evaluations demonstrate that AQC achieves a 70% improvement in key exchange efficiency, a 50% reduction in computational load, and a 95% resilience rate against quantum attacks compared to conventional encryption methods. Additionally, the integration of QRNGs enhances cryptographic key entropy, while AI-driven anomaly detection enables proactive threat mitigation. This framework is particularly suited for next-generation IoT applications, including smart grids, autonomous vehicles, and industrial automation, where security, scalability, and energy efficiency are critical. By combining quantum-resistant algorithms with adaptive security mechanisms, AQC provides forward secrecy, resistance to quantum adversaries, and robust authentication, ensuring long-term protection for IoT ecosystems in the post-quantum era. The findings underscore AQC’s potential as a foundational security architecture for future quantum-safe IoT networks.

Most currently used cryptographic tools for protecting data are based on certain computational assumptions, which makes them vulnerable with respect to technological and algorithmic developments, such as quantum computing. One existing option to counter this potential threat is quantum key distribution, whose security is based on the laws of quantum physics. Quantum key distribution is secure against unforeseen technological developments. A second approach is post-quantum cryptography, which is a set of cryptographic primitives that are believed to be secure even against attacks with both classical and quantum computing technologies. From this perspective, this study reviews recent progress in the deployment of the quantum-secured infrastructure based on quantum key distribution, post-quantum cryptography, and their combinations. Various directions in the further development of the full-stack quantum-secured infrastructure are also indicated. Distributed applications, such as blockchains and distributed ledgers, are also discussed.

ABSTARCT The rapid proliferation of smart home Internet of Things (IoT) technologies has transformed residential environments through intelligent automation, remote monitoring, and data driven decision making. Alongside these benefits, security risks have intensified due to advances in large scale quantum computing, which threaten the cryptographic foundations of current IoT systems. Widely deployed public key algorithms such as RSA and Elliptic Curve Cryptography are vulnerable to quantum attacks enabled by Shor’s algorithm, raising serious concerns regarding long term confidentiality, authentication, and trust in smart home ecosystems. To address this challenge, two major quantum resilient security paradigms have emerged: Post Quantum Cryptography (PQC) and Quantum Key Distribution (QKD). This paper presents a structured comparative study of PQC and QKD within smart home IoT environments, evaluating architectural compatibility, computational and energy constraints, scalability, deployment cost, communication models, and security guarantees. Realistic smart home scenarios including smart locks, surveillance cameras, and resource constrained sensor networks are examined to assess practical feasibility. The analysis demonstrates that while QKD offers information theoretic security under ideal conditions, its reliance on specialized quantum hardware and dedicated infrastructure makes it unsuitable for consumer smart homes. In contrast, PQC provides a scalable, software based, and cost effective approach that integrates seamlessly. Keywords: Post-Quantum Cryptography, Quantum Key Distribution, Smart Home IoT, Quantum Security, IoT Cryptography.

In the modern world, the financial sector faces a wide range of extraordinary events, from market shocks and geopolitical tensions to pandemics and cyberattacks. These diverse challenges significantly impact banks. Recently, particular attention has been drawn to the influence of artificial intelligence (AI) and quantum computing (QC) technologies on the stability of the financial system. This article analyzes the potential areas of impact of quantum technologies on the financial sphere in general and the resilience of financial institutions in particular.It's determined that quantum technologies can simultaneously pose both threats and new opportunities. Specifically, the article analyzes the potential of quantum technologies to break existing cryptographic algorithms that protect the confidential data of financial institutions' clients. This threat is exacerbated by the possibility of "harvest now, decrypt later" attacks, where malicious actors intercept data today with the intention of decrypting it in the future. This presents challenges and threats for online/mobile banking, payment operations, and corporate communications. Among the positive impacts of quantum technologies on banking, the article highlights improved financial risk assessment, particularly enhanced accuracy in stress testing, portfolio management, and derivatives pricing, by solving problems inaccessible to classical computing. The potential of quantum machine learning for fraud detection is also noted. Attention is given to the financial sector's response to these challenges. Initiatives for developing quantum-resistant (post-quantum) cryptography are considered as the primary method for mitigating the risks associated with the proliferation of quantum computing, along with new cryptographic protocols and quantum key distribution as a new opportunity to enhance security. The article emphasizes the responsibility of central banks in forming quantum-readiness strategies, including investments in post-quantum cryptography, expertise development, and the adaptation of regulatory frameworks. The conclusion drawn is that although the immediate benefits of quantum technologies may be modest, their long-term transformative potential for the financial sector is immense.

Classical cryptographic systems are increasingly challenged by advances in computing power and new algorithmic techniques, particularly with the rise of quantum computing, which threatens the security of current encryption methods. This has spurred interest in quantum-resistant cryptography, aimed at creating algorithms that can withstand attacks from quantum computers. Traditionally, secure key transport over alternate channels has been a significant challenge, but quantum mechanics offers a solution. Quantum Key Distribution (QKD) is a revolutionary method for secure communication that leverages quantum principles. Unlike traditional methods, QKD provides unconditional security, with key security ensured by the laws of physics rather than computational difficulty. The BB84 protocol, introduced in 1984 by Bennett and Brassard, is a leading QKD scheme known for its simplicity and effectiveness in generating eavesdropping-resistant cryptographic keys. It facilitates secure key transport over alternate channels. This documentation aims to advance QKD security by practically implementing and analyzing the BB84 protocol. Through detailed theoretical analysis, simulation studies, and experimental validation, the practical impacts, and limitations of BB84-based QKD systems are examined. Additionally, a practical implementation of quantum key distribution using a sudoku key demonstrates the process's simplicity and effectiveness. These findings are expected to pave new paths in the field of cryptanalysis in the emerging Quantum Age.

Abstract: This book explores the convergence of quantum communication technologies and decentralized blockchain frameworks, offering a comprehensive guide to building secure, scalable, and resilient quantum communication infrastructures. With quantum computing threatening classical cryptographic systems, there is an urgent need to develop quantum-resistant and quantum-native protocols. The book investigates post-quantum cryptographic primitives, quantum key distribution (QKD), and blockchain-integrated quantum consensus models. Special emphasis is given to the design and deployment of hybrid quantum-classical nodes, real-time authentication systems, and decentralized identity protocols. Through detailed architectural models and case studies in finance, healthcare, and national security, this work lays the groundwork for resilient, secure data exchange networks of the future. It aims to inform academics, technologists, policymakers, and quantum engineers navigating this technological frontier. Keywords: quantum blockchain, decentralized networks, quantum key distribution, post-quantum cryptography, secure communication, consensus algorithms, hybrid systems, protocol design, resilient infrastructure, quantum internet

Quantum computing challenges the long-term security assumptions of blockchain systems that rely on classical public-key cryptography, motivating the adoption of post-quantum cryptography and quantum key distribution (QKD). This review maps research fronts at the intersection of blockchain and quantum-safe security, linking threat assumptions to post-quantum mechanisms, blockchain layers, and QKD positioning. Records were retrieved from Scopus and Web of Science using a two-block query and filtered through a PRISMA-guided workflow for bibliometric mapping. The final corpus comprises 648 journal articles and shows accelerated publication growth after 2023, with scientific production concentrated in a small set of leading countries. Keyword structures indicate that IoT-centric deployments dominate the semantic backbone, where authentication and intelligent methods co-occur with blockchain security primitives, while post-quantum and privacy-preserving constructs form a cohesive technical stream. QKD appears as a distinct but more specialized theme, typically discussed at the system level and shaped by infrastructure and scalability constraints. Overall, the literature is moving from conceptual risk articulation toward engineering integration; however, progress is limited by inconsistent reporting of threat models, post-quantum parameter sets, and ledger-level cost trade-offs, highlighting the need for auditable and reproducible evaluation.

The rapid advancement of digital technologies, particularly the Internet of Things (IoT) and quantum computing (QC), is reshaping modern military operations by enhancing real-time data collection, autonomous decision-making, and situational awareness. IoT-enabled systems, such as UAVs, battlefield sensors, and smart logistics, provide military forces with operational superiority but also introduce significant cybersecurity risks, including espionage, cyber sabotage, and unauthorized access. The emergence of QC further complicates this landscape, as quantum algorithms can break traditional encryption protocols, threatening the security of military communications and IoT infrastructure. However, quantum technologies also offer revolutionary cybersecurity solutions, such as Quantum Key Distribution (QKD) and Post-Quantum Cryptography (PQC), which leverage the principles of quantum mechanics to ensure secure communication. Despite these advancements, challenges such as the technological maturity of quantum solutions, high implementation costs, and global competition in quantum research pose obstacles to widespread military adoption. This chapter explores the interplay between QC and military IoT security, addressing both the vulnerabilities of IoT systems and the potential of quantum-enhanced security frameworks. By integrating quantum-safe cryptographic techniques, defence organizations can fortify military IoT infrastructure, mitigate cyber threats, and maintain strategic superiority in an era of increasing digital warfare.

Emerging network applications are based on collaborative environments that rely on the secure group-based communication paradigm. These protocols use traditional public-key cryptography (PKC) for authenticating the group members and exchange secret keys. However, the foreseeable breakthrough of quantum computers represents a risk for the secure systems based on PKC. In order to prepare for such an event, quantum-secure group-based communications must be established. Post-quantumcryptography (PQC) and quantum-key distribution (QKD) are two quantum-resistant technologies that can be used for enabling the long term security in such collaborative environments. This work proposes four quantum-secure group-based communication solutions, based on contributory and decentralized protocols. PQC and hybrid technologies (PQC/QKD) are explored. The solutions use PQC Key-exchange algorithms or QKD protocols (decoy-BB84 and T12) for key generation and PQC signature algorithms for authentication. For the first time hybrid schemes for group-based technologies are designed and explored. Results show that the group-based decentralized protocol (PQC SLIMCAST) outperforms the contributory protocol PQC GAKE. The PQC-based approaches have a better performance than the QKD versions.

As artificial intelligence (AI) systems increasingly underpin critical applications in healthcare, finance, defense, and infrastructure, ensuring their security has become paramount. However, the rapid advancement of quantum computing poses a significant threat to classical cryptographic schemes that currently safeguard these systems. Quantum algorithms such as Shor’s and Grover’s threaten to undermine the confidentiality, integrity, and authentication of data and models that AI systems depend on. In this context, Post-Quantum Cryptography (PQC) has emerged as a crucial area of research aimed at developing cryptographic algorithms that are secure against both classical and quantum adversaries. This paper investigates the intersection of quantum computing threats and AI system vulnerabilities, highlighting how current security mechanisms may fail in a post-quantum era. We explore various categories of PQC—including lattice-based, hash-based, and multivariate polynomial cryptography—and evaluate their applicability to securing AI systems, particularly in scenarios such as model distribution, federated learning, data encryption, and communication in AI-enabled edge and IoT environments. Through analysis of emerging use cases and proposed architectures, the paper outlines how PQC can be integrated into the AI lifecycle to mitigate quantum-era threats. It also identifies key challenges such as computational overhead, integration complexity, and standardization gaps. The study concludes by outlining future research opportunities, including the development of efficient PQC protocols tailored to AI workloads, the creation of quantum-resilient AI pipelines, and the importance of interdisciplinary collaboration to secure AI’s future.

As artificial intelligence (AI) systems increasingly underpin critical applications in healthcare, finance, defense, and infrastructure, ensuring their security has become paramount. However, the rapid advancement of quantum computing poses a significant threat to classical cryptographic schemes that currently safeguard these systems. Quantum algorithms such as Shor’s and Grover’s threaten to undermine the confidentiality, integrity, and authentication of data and models that AI systems depend on. In this context, Post-Quantum Cryptography (PQC) has emerged as a crucial area of research aimed at developing cryptographic algorithms that are secure against both classical and quantum adversaries. This paper investigates the intersection of quantum computing threats and AI system vulnerabilities, highlighting how current security mechanisms may fail in a post-quantum era. We explore various categories of PQC—including lattice-based, hash-based, and multivariate polynomial cryptography—and evaluate their applicability to securing AI systems, particularly in scenarios such as model distribution, federated learning, data encryption, and communication in AI-enabled edge and IoT environments. Through analysis of emerging use cases and proposed architectures, the paper outlines how PQC can be integrated into the AI lifecycle to mitigate quantum-era threats. It also identifies key challenges such as computational overhead, integration complexity, and standardization gaps. The study concludes by outlining future research opportunities, including the development of efficient PQC protocols tailored to AI workloads, the creation of quantum-resilient AI pipelines, and the importance of interdisciplinary collaboration to secure AI’s future.

Cryptographic algorithms are crucial for secure communication in the Internet of Things (IoT). Quantum computers threaten public key cryptography algorithms like RSA (Rivest, Shamir, Adleman) and Diffie-Hellman (DH) key exchange schemes, which are widely in use today. As cryptographic algorithms are the foundation of secure internet communication, the development of Quantum Key Distribution (QKD) and Post-Quantum Cryptography (PQC) is essential to protect transactions over the internet. However, solutions like Quantum Key Distribution require heavy infrastructure. So, it is not feasible for the Internet of Things with fewer resources in computing power and form factor. Post-Quantum Cryptography is helpful on these devices. But, it needs further developments and improvements. This paper analyzes cryptography algorithms and protocols of IoT with different categories. Integrated PQC of National Institute of Standards and Technology (NIST) third level finalists on Raspberry Pi 4 (RPI4) board with Linux operating system. The performance of Post-Quantum Cryptography schemes for IoT has been evaluated. Finally, a Post-Quantum Cryptography scheme has been suggested for the Internet of Things based on the performance analysis.