PQC Planner: Post-Quantum Cryptographic Migration Planner

Various network optimization and management goals in cloud data centers can be achieved by re-mapping VMs to the substrate servers. Live VM migration is used to implement such re-mapping by moving VMs from the initial servers to the target ones. For efficiency and usability considerations, these migration tasks are expected to be completed as soon as possible, which can be achieved by planning multiple VMs to be migrated simultaneously. However, the available resources of computation and bandwidth limits the number of VMs that can be migrated at the same time. Besides, the available resources change with the progress of migration process, which makes VM migration planning a challenge problem. Considering both resources constraints and the dependence between the migration plan and the total migration time, in this paper, we investigate the problem of virtual machine migration planning to minimize the total migration time. We formulate VM migration planning as an optimization problem considering both computation and bandwidth constraints. Our formulation is based on a step-by-step migration scheme, where multiple VMs can be migrated simultaneously as long as the resource constraints are satisfied. The solution of the optimization problem outputs the migration plan which achieves the minimum time to finish the migration task. Moreover, we verify the effectiveness of the optimal migration plan through extensive simulations and comparison with the best algorithm in existing works.

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

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.

Hybrid key encapsulation is in the process of becoming the de-facto standard for integration of post-quantum cryptography (PQC). Supporting two cryptographic primitives is a challenging task for constrained embedded systems. Both contemporary cryptography based on elliptic curves or RSA and PQC based on lattices require costly multiplications. Recent works have shown how to implement lattice-based cryptography on big-integer coprocessors. We propose a novel hardware design that natively supports the multiplication of polynomials and big integers, integrate it into a RISC-V core, and extend the RISC-V ISA accordingly. We provide an implementation of Saber and X25519 to demonstrate that both lattice- and elliptic-curve-based cryptography benefits from our extension. Our implementation requires only intermediate logic overhead, while significantly outperforming optimized ARM Cortex M4 implementations, other hardware/software codesigns, and designs that rely on contemporary accelerators.

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.

Cryptography is the practice of securing information through the use of codes, ciphers, and other methods of encryption. It is an essential aspect of modern communication, enabling the secure transmission of data over networks and protecting sensitive information from unauthorized access. Cryptography has been used throughout history to protect messages from interception and decipherment. In ancient times, cryptography was used by military leaders and diplomats to communicate confidential information. Over time, cryptographic techniques have become more sophisticated, and modern cryptography now employs complex algorithms and mathematical principles.Today, cryptography is used in various applications, including online banking, e-commerce, secure messaging, and government communication. Cryptography also plays a critical role in securing sensitive information such as medical records, personal data, and intellectual property.As technology continues to evolve, the importance of cryptography will only increase. Cryptography ensures the confidentiality, integrity, and authenticity of data, and it is an essential tool for protecting digital assets and maintaining trust in the online world. Literature Review: Cryptography has been a subject of interest in computer science and mathematics for decades. The literature on cryptography is vast and covers a wide range of topics, including encryption algorithms, key management, and protocols for secure communication. One of the earliest and most well-known encryption algorithms is the Caesar cipher, which was used by Julius Caesar to encode his messages. Since then, numerous encryption techniques have been developed, including symmetric-key cryptography and public-key cryptography.Symmetric-key cryptography involves the use of a single key for both encryption and decryption, while public-key cryptography uses two keys, one for encryption and one for decryption.In recent years, research on post-quantum cryptography has gained significant attention due to the potential threat quantum computers pose to current encryption methods. Post- quantum cryptography aims to develop algorithms that are resistant to quantum attacks.

FALCON is a signature selected for standardisation of the new Post-Quantum Cryptography (PQC) primitives by the National Institute of Standards and Technology (NIST). However, it remains a challenge to define efficient countermeasures against side-channel attacks (SCA) for this algorithm. FALCON is a lattice-based signature that relies on rational numbers, which is unusual in the cryptography field. Although recent work proposed a solution to mask the addition and the multiplication, some roadblocks remain, most noticeably, how to protect the floor function. In this work, we propose to complete the first existing tests of hardening FALCON against SCA. We perform the mathematical proofs of our methods as well as formal security proofs in the probing model by ensuring Multiple Input Multiple Output Strong Non-Interference (MIMO-SNI) security. We provide performances on a laptop computer of our gadgets as well as of a complete masked FALCON. We notice significant overhead in doing so and discuss the deployability of our method in a real-world context.

This study examines the convergence of rapid Central Bank Digital Currency adoption and the growing threat that quantum computing poses to existing cryptographic systems. As digital sovereign currencies expand globally, with many economies actively exploring or piloting CBDCs, the vulnerability of classical public key cryptography to quantum attacks creates an urgent need for quantum resistant solutions. The research responds to this challenge by developing an evaluation framework focused on secure and interoperable cross border CBDC systems in a post quantum environment. Using desk based computational analysis and simulation methods suitable for remote researchers, the study evaluates lattice based algorithms standardized by the National Institute of Standards and Technology, specifically ML KEM for key encapsulation and ML DSA for digital signatures. The analysis confirms strong quantum resistance against known quantum algorithms, effectively removing harvest now decrypt later risks for future transactions. Interoperability assessments show that ISO 20022 with cryptographic abstraction is well suited for retail CBDC systems, while bridge based architectures such as BIS mBridge are more effective for wholesale settlements. Performance testing on thousands of simulated transactions indicates that post quantum protocols are feasible for wholesale use but introduce significant computational and bandwidth overheads that limit immediate retail scalability without hardware acceleration. Overall, the findings support a phased migration strategy that combines classical and post quantum cryptography in the near term, guided by cryptographic agility. The study provides practical insights for central banks seeking to balance security, efficiency, and cross border compatibility in an evolving quantum threat landscape.

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.

Remote Health Interventions: Effectiveness, Cost, and Cost-Effectiveness Considerations.

The Internet of Things (IoT) has revolutionized the way devices communicate and interact, enabling seamless integration into various aspects of daily life by billions of connected devices equipped with small, embedded controllers that monitor and manage our increasingly interconnected world. The swift growth of IoT devices has led to significant concerns about data security and privacy. Traditional cryptographic algorithms, usually lightweight cryptography, are effective against classical computing threats. However, they are vulnerable to attacks from emerging quantum computing technologies, which can quickly solve the mathematically hard problems used in classical cryptography. Post-Quantum Cryptography (PQC) offers promising solution by providing cryptographic primitives resistant to quantum attacks. This chapter addresses challenges posed by resource constrained IoT devices, like limited processing power and memory. It also explores the integration of PQC algorithms suitable for IoT environments, considering factors like computational efficiency and resistance to quantum attacks.

In ad-hoc Grids where the availability of resources and tasks changes over the time, distributing the tasks among the scarce resources in a balanced way is a challenging task. In this paper, we present how using an economic-based approach, the tasks can be distributed evenly among the scarce resources. Such that all nodes which have tasks to be executed, receive more or less equal utilization from the Grid resources. We consider a continuous double auction protocol as the economic approach to share idle cpu cycles among the nodes in a local ad-hoc Grid. Each node is given a limited budget when joining the Grid. The node can use it to buy required resources or increases its budget by selling idle resources. Consumers and producers of resources determine their bid and ask prices using a dynamic pricing strategy and the auctioneer adopts a discriminatory pricing policy which sets the transaction price individually for each matched buyer-seller pair. We experiment in a network where the resources are scarce and the tasks outnumber the resources. The spread of task utilization at individual nodes and the level of load balancing are measured and compared with a non-economic approach. The results show that economic-based approach provides a fair and balanced basis for access to Grid resources for everyone while in the same time gives a satisfactory level of system performance.

The rapid deployment of the Internet of Things (IoT) brought some interesting topics into the spotlight, one of which is low-power design. IoT devices are usually deployed in environments where access to an electricity network is not feasible and therefore have to be supplied by a battery. Despite the limited energy budget in this setting, many relevant applications require long device runtimes. Additionally, in order to establish secure connections to other IoT devices, cryptographic primitives are required to safely transmit data. Since the devices are physically accessible, enabling adversaries to mount all sorts of physical attacks, physically secure implementations are inevitable. In this study, we evaluate the energy consumption of cryptographic primitives on a custom 65 nm ASIC with different design architectures ranging from unrolled to serialized implementation. In each design architecture, we compare the consumed energy of different crypto cores. We also examine the energy consumption of different masking schemes up to third-order secure realizations of various block ciphers. Further, in our practical investigations, we explore the energy consumption overhead of countermeasures against fault-injection attacks under different adversary models providing the first practical results on real silicon for protected implementations.

In this work, we propose a local search-based strategy to determine high-quality allocation of vaccines under restricted budgets and time periods. For this, disease spread is modeled as a SEAIR pandemic model. Subgroups are used to understand and evaluate movement restrictions and their effect on interactions between geographical divisions. A tabu search heuristic method is used to determine the number of vaccines and the groups to allocate them in each time period, minimizing the maximum number of infected people at the same time and the total infected population. Available data for COVID-19 daily cases was used to adjust the parameters of the SEAIR models in four study cases: Austria, Belgium, Denmark, and Chile. From these, we can analyze how different vaccination schemes are more beneficial for the population as a whole based on different reproduction numbers, interaction levels, and the availability of resources in each study case. Moreover, from these experiments, a strong relationship between the defined objectives is noticed.