Post quantum computing – cryptography

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.

This article mainly discusses the history of progress regarding the legislation and updates through scrutiny, its current architecture, and its standards applied around the world, such as eIDAS and eIDAS 2.0, which are used not only as technical but also as purely political standards. The penetration of the digital economy has largely promoted the evolution of cyber platforms for public and private use, so that e-signatures have become one of the pillars in the national IT architecture. 1) Legislation The e-signature operations in Türkiye are regulated by Electronic Signature Law No. 5070 and its secondary regulations. However, today, the infrastructure groundwork relies heavily on RSA-based cryptography. RSA is attracting greater and more debate these days, with concerns about whether it will continue to be useful given the increasing importance of security requirements for mobile devices, performance expectations, and the threat posed by quantum computing. This article also examines the extent to which Turkish law is compatible with the EU regulation of compliance. In this paper, we study whether the Turkish legislation complies with the European legislation. This covers security, performance, key size, and support for RSA and Elliptic Curve Cryptography (ECC) algorithms. This paper discusses technical, institutional, and legal requirements for the transition of the national e-signature infrastructure to ECC. Furthermore, ECC’s contribution is evaluated in terms of Post-Quantum Cryptography (PQC), and a roadmap is suggested for transitioning to hybrid (ECC + PQC) architectures. Finally, policy and technical suggestions are proposed to facilitate international electronic and mobile signature interoperability under eIDAS 2.0.

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

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.

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.

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.

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.

Abstract: This book presents a comprehensive exploration of quantum cryptography as an emergent paradigm in secure communications, enhanced through the integration of quantum computing and machine learning methodologies. Grounded in the principles of quantum mechanics—superposition, entanglement, and the no-cloning theorem—it develops a conceptual and mathematical framework for information-theoretic security resistant to both classical and quantum adversaries. The work identifies the limitations of classical cryptographic systems in the advent of large-scale quantum computation and proposes hybrid architectures that leverage machine learning for adaptive threat detection, protocol optimization, and anomaly classification in quantum key distribution (QKD) environments. Methodologically, the text synthesizes theoretical analysis, formal security proofs, and empirical evaluation using both quantum simulation platforms and experimental testbeds. Key results demonstrate that quantum–machine learning synergies can improve key generation rates, enhance noise tolerance, and accelerate real-time countermeasure deployment. The implications extend to the design of scalable, interoperable cryptographic systems compatible with emerging quantum internet infrastructures, while also addressing ethical and regulatory considerations in deployment. By combining rigorous academic analysis with practical implementation insights, this book establishes a scholarly and applied foundation for next-generation secure communication systems in the quantum era. Keywords Quantum cryptography, quantum key distribution, quantum computing, machine learning, quantum machine learning, cryptographic security, post-quantum cryptography, hybrid architectures, adaptive protocol optimization, information-theoretic security, secure communications, quantum internet, ethical implications in cryptography

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.

Advances in quantum computing and particularly their impact on security and privacy is a topic of increasing importance to IT practitioners. The authors provide a readily understandable introduction to quantum computing, as well as post-quantum cryptography. They also explain post-quantum cryptographic solutions such as quantum-resistant algorithms and quantum key distribution. Lastly, the suitability of these solutions is addressed with a focus on their impact on the modern cryptographic infrastructure and applicability to the IT profession.

As federated learning (FL) keeps dominating the way in privacy-preserving machine learning (ML), notably in finance, its long-term sustainability is confronted with the approaching challenge of quantum computing. The introduction of quantum computing poses a challenge to traditional cryptographic technique on which FL relies RSA, elliptic curve cryptography (ECC), and some homomorphic encryption (HE) methods applied for encrypting model updates during training rendering this chapter to explore the interplay between the threat of quantum computing and the FL architectures, with emphasis on the implications this interaction introduces to cybersecurity and privacy in finance applications. Quantum computers are theoretically capable of solving hard math problems that have been regarded as computationally intractable for quantum computers. The well-known algorithms like Shor’s and Grover’s provides serious risk to the cryptographic procedures FL pipelines depends on. The finance sector, by its nature involving sensitive data and dependence on secure, distributed ML systems, is particularly vulnerable. The chapter begins by summarizing the fundamentals of FL and current encryption methods adapted to protect FL workflows. It then shifts towards the essence of quantum computing, emphasizing on the notable algorithms that threaten FL. We also explore potential attack points through which quantum computing could attack FL, e.g., model inversion attacks, poisoning attacks facilitated by quantum capabilities, and threats to secure aggregation. Post-quantum cryptography (PQC) is also presented as a potential counterattack, followed by a discussion of its use case in FL platforms. This chapter attempts to close the gap between FL and quantum computing threats to the financial sector. It is an introduction to practitioners and researchers to revisit examining security assumptions in FL and move towards the quantum-augmented cyber threat model.

Quantum computing is an evolution of classical computing, capable of solving problems that are competitive enough to break the existing cryptographic primitives upon which current blockchain systems are based. Popular schemes like RSA, ECDSA, and SHA-256 can be compromised by quantum algorithms (Shor's and Grover's), raising questions about the security and trustworthiness of blockchain-based applications in finance, healthcare, and supply chains. Many current approaches focus on isolated aspects of the blockchain, such as cryptographic primitives or key exchange, without a comprehensive strategy that can guarantee end-to-end security in the face of a quantum threat. Finally, traditional consensus mechanisms such as Proof-of-Work and Proof-of-Stake are vulnerable to Sybil attacks, centralization, and leader-selection bias. When the adversary has access to a quantum computer, these issues become significantly worse. In this paper, we present QuantumShield-BC, a modular blockchain framework incorporating post-quantum cryptographic signatures, quantum key distribution (QKD), and a novel Quantum Byzantine Fault Tolerance (Q-BFT) consensus mechanism driven by quantum random number generation (QRNG) to address these challenges. QKD: The system supports tamper-proof key exchange, quantum-resilient consensus among validator nodes, and secure transaction signing. Experimental evaluation demonstrates that QuantumShield-BC achieves low consensus latency and high throughput, while providing perfect security against simulated attacks from Shor's and Grover's algorithms. The proposed framework eradicates the Sybil attack effectiveness up to 0%, eliminates replay and MITM vulnerabilities, and achieves an average throughput of over 7,000 transactions per second with 100 validators, orders of magnitude better than classical blockchain systems. The importance of each quantum part to the system's robustness is also demonstrated using an ablation study. With its unique ability to provide a post-quantum framework for high-assurance, general-purpose, scalable, and interoperable blockchain networks resistant to quantum-inspired attacks or quantum retrieval, QuantumShield-BC is practical for deployment in critical infrastructure and digital trust ecosystems where performance and a future-proof foundation are essential.

Quantum computing has the capability of parallel computing and is superior to classical computing in solving some specific problems. Once a large-scale quantum computer is developed, the security of classical cryptographic algorithms and protocols, which is based on the assumption of computational complexity, will be severely challenged. Quantum cryptography is a new cryptosystem; its security is based on the principles of quantum mechanics, and can resist the attack of quantum computing. This paper focuses on the nearly 40 years development of quantum cryptographic protocols, including quantum key distribution (QKD), quantum secure direct communication, quantum secret sharing, quantum identity authentication, two-party secure computation, and quantum private query, and summarizes the problems in the process of development. The analysis shows that the quantum cryptographic protocols are in an unbalanced state: QKD is far ahead of other protocols and other protocols are difficult to achieve breakthroughs. In the future, practical quantum protocols for digital signature and two-party secure computation are core issues that needs to be addressed urgently. Therefore, research on quantum and post-quantum cryptography should be conducted synchronously, cross-over study and talent cultivation for the quantum science and cryptography disciplines should be strengthened, and the examination and evaluation mechanism of relevant basic research needs to be optimized.

Cryptographic security is essential for ensuring data integrity and secure communication. Traditional encryption methods such as RSA and elliptic curve cryptography (ECC), while widely used, suffer from high computational complexity, large key sizes, and vulnerability to evolving attack strategies. This paper introduces geometric mean labeling(GML), a novel graph-based cryptographic technique that enhances encryption efficiency, key management, and security. Unlike RSA, which relies on prime factorization, or ECC, which depends on elliptic curve logarithms, GML applies geometric mean-based transformations to encrypt data using structured graph relationships, making it computationally efficient. Specifically, GML achieves encryption in just 0.085 ms with a 512-bit key, compared to 600 ms (RSA, 2,048-bit) and 30 ms (ECC, 256-bit), leading to a 99.99% speed improvement over RSA and 99.7% over ECC. Theoretical analysis confirms that GML operates with a computational complexity of O(V3), making it scalable for large-scale encryption while maintaining strong security against brute-force and chosen-plaintext attacks. Experimental validation was conducted on an Intel i7-based system, confirming the efficiency and reliability of GML for real-world applications such as IoT security and cloud encryption. By integrating GML into modern cryptographic frameworks, this study provides a scalable, efficient, and future-ready encryption solution, with potential applications in post-quantum cryptography.

The expansion of Internet of Things (IoT) ecosystems has created a high demand for secure cryptographic solutions, even in a future with quantum computing capabilities. Traditional mappings, such as RSA or Elliptic Curve Cryptography (ECC), are expected to be broken by Shor's algorithm, driving the realization of post-quantum cryptography (PQC). This work presents a simulative and prototypical framework for assessing PQC integration in IoT communication. With the liboqs library and NS-3 network simulator, along with the Python scripting language, we implement both NIST-standardized algorithms, such as Dilithium (for signatures) and Kyber (for key encapsulation), as well as the classical RSA and ECC baselines. IoT networks of 50-500 virtual nodes are simulated based on IEEE 802.15.4/6LoWPAN with RPL routing. Performance attributes, including encryption/decryption time, key length, packet delivery ratio, latency, and energy consumption, are collected and evaluated. Preliminary results indicate that PQC incurs additional handshake and key overhead, but is relatively practical, with an average overhead of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$15-25 ~\text{ms}$</tex> per processed secure transaction. The effort provides a replicable testbed, showcasing what we consider the best and worst PQC has to offer for resource-constrained IoT. Targeted at master's students and researchers, this book provides an applied approach to investigate quantum-resilient security in IoT. It encourages future expansion to hardware-in-the-loop validation on embedded devices.