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M.G.A. Butenaerts
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Securing Confidential Smart Contracts with Post Quantum Cryptography
How to sideline the quantum computers
Quantum attacks threaten the public-key cryptography that underpins modern distributed systems, including permissioned blockchains. This thesis investigates the practicality of post-quantum cryptography (PQC) in enterprise settings by integrating CRYSTALS-Kyber (Key Encapsulation Mechanism) and CRYSTALS-Dilithium (digital signatures) into a Fabric-based banking application. A protocol is designed for account creation and authenticated transactions where clients register with a Kyber public key, and the server encapsulates a shared secret used to authenticate the transactions. All balance, deposit, withdrawal, and transfer messages are signed with Dilithium and verified. The implementation comprises server, client, and chaincode components, integrated via Fabric Private Chaincode (FPC), and performance is evaluated against an RSA baseline in terms of key, ciphertext, and signature sizes.
The evaluation demonstrates that PQC integration is feasible with modest overheads. The replacement from RSA to Dilithium for transaction authentication and Kyber for key establishment performs better in most situations and maintains system throughput within operational bounds. Predictable trade-offs are observed between larger key and signature artifacts and reduced verification complexity. Message sizes for each cryptographic stage (key generation, encapsulation/decapsulation, signature/verification) are quantified. The system resists chosen-ciphertext and chosen-message attacks under the Module-LWE/SIS assumptions and achieves strong unforgeability for application messages.
This work provides an end-to-end blueprint covering APIs, message formats, chaincode logic, and deployment scripts for migrating Fabric-style ledgers to post-quantum security and ideas to improve upon the work in the future. ...
The evaluation demonstrates that PQC integration is feasible with modest overheads. The replacement from RSA to Dilithium for transaction authentication and Kyber for key establishment performs better in most situations and maintains system throughput within operational bounds. Predictable trade-offs are observed between larger key and signature artifacts and reduced verification complexity. Message sizes for each cryptographic stage (key generation, encapsulation/decapsulation, signature/verification) are quantified. The system resists chosen-ciphertext and chosen-message attacks under the Module-LWE/SIS assumptions and achieves strong unforgeability for application messages.
This work provides an end-to-end blueprint covering APIs, message formats, chaincode logic, and deployment scripts for migrating Fabric-style ledgers to post-quantum security and ideas to improve upon the work in the future. ...
Quantum attacks threaten the public-key cryptography that underpins modern distributed systems, including permissioned blockchains. This thesis investigates the practicality of post-quantum cryptography (PQC) in enterprise settings by integrating CRYSTALS-Kyber (Key Encapsulation Mechanism) and CRYSTALS-Dilithium (digital signatures) into a Fabric-based banking application. A protocol is designed for account creation and authenticated transactions where clients register with a Kyber public key, and the server encapsulates a shared secret used to authenticate the transactions. All balance, deposit, withdrawal, and transfer messages are signed with Dilithium and verified. The implementation comprises server, client, and chaincode components, integrated via Fabric Private Chaincode (FPC), and performance is evaluated against an RSA baseline in terms of key, ciphertext, and signature sizes.
The evaluation demonstrates that PQC integration is feasible with modest overheads. The replacement from RSA to Dilithium for transaction authentication and Kyber for key establishment performs better in most situations and maintains system throughput within operational bounds. Predictable trade-offs are observed between larger key and signature artifacts and reduced verification complexity. Message sizes for each cryptographic stage (key generation, encapsulation/decapsulation, signature/verification) are quantified. The system resists chosen-ciphertext and chosen-message attacks under the Module-LWE/SIS assumptions and achieves strong unforgeability for application messages.
This work provides an end-to-end blueprint covering APIs, message formats, chaincode logic, and deployment scripts for migrating Fabric-style ledgers to post-quantum security and ideas to improve upon the work in the future.
The evaluation demonstrates that PQC integration is feasible with modest overheads. The replacement from RSA to Dilithium for transaction authentication and Kyber for key establishment performs better in most situations and maintains system throughput within operational bounds. Predictable trade-offs are observed between larger key and signature artifacts and reduced verification complexity. Message sizes for each cryptographic stage (key generation, encapsulation/decapsulation, signature/verification) are quantified. The system resists chosen-ciphertext and chosen-message attacks under the Module-LWE/SIS assumptions and achieves strong unforgeability for application messages.
This work provides an end-to-end blueprint covering APIs, message formats, chaincode logic, and deployment scripts for migrating Fabric-style ledgers to post-quantum security and ideas to improve upon the work in the future.
Because of the growing presence of artificial intelligence, developers are looking for more efficient methods to construct machine learning algorithms. Program synthesizers allow us to produce algorithms consisting of scalers, feature selection and classifiers. Each of these pipelines is a potential solution to the given machine learning task. The goal of this synthesizer was to find the best-suited pipeline for the problem, with a genetic search algorithm. The structure of the pipelines makes it easy to implement the cross-over and mutation properties of a genetic algorithm, as the pipelines and different algorithms very much resemble chromosomes and genes. Experiments were designed to measure the accuracies and runtimes of the synthesizer with the intent to compare them to the results of other synthesizers based on different search algorithms. The comparisons made could prove whether machine learning synthesizers are a viable solution to the mentioned development problem.
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Because of the growing presence of artificial intelligence, developers are looking for more efficient methods to construct machine learning algorithms. Program synthesizers allow us to produce algorithms consisting of scalers, feature selection and classifiers. Each of these pipelines is a potential solution to the given machine learning task. The goal of this synthesizer was to find the best-suited pipeline for the problem, with a genetic search algorithm. The structure of the pipelines makes it easy to implement the cross-over and mutation properties of a genetic algorithm, as the pipelines and different algorithms very much resemble chromosomes and genes. Experiments were designed to measure the accuracies and runtimes of the synthesizer with the intent to compare them to the results of other synthesizers based on different search algorithms. The comparisons made could prove whether machine learning synthesizers are a viable solution to the mentioned development problem.