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Federated reinforcement learning for edge computing optimization – Complete Phd and Masters Thesis

Federated reinforcement learning for edge computing optimization – Complete Phd and Masters Thesis

[ad_1] Introduction With the rapid growth of Internet of Things (IoT) devices and the increasing demand for real-time data processing, edge computing has emerged as a promising solution to address the limitations of cloud computing.…

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Distributed ledger technology for decentralized finance (DeFi) – Complete Phd and Masters Thesis

Distributed ledger technology for decentralized finance (DeFi) – Complete Phd and Masters Thesis

[ad_1] Introduction Distributed ledger technology (DLT), which emerged as the underlying technology of cryptocurrencies like Bitcoin, has gained significant attention in recent years. Particularly, the application of DLT in decentralized finance (DeFi) has the potential…

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Homomorphic encryption for secure image processing – Complete Phd and Masters Thesis

Homomorphic encryption for secure image processing – Complete Phd and Masters Thesis

[ad_1] Introduction Homomorphic encryption is a revolutionary technology that allows computations to be performed directly on encrypted data without the need to decrypt it. This breakthrough in cryptography has significant implications for secure image processing,…

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Zero-knowledge proofs for privacy-preserving smart metering – Complete Phd and Masters Thesis

Zero-knowledge proofs for privacy-preserving smart metering – Complete Phd and Masters Thesis

[ad_1] Introduction Zero-knowledge proofs have gained significant attention in recent years for their potential to enhance privacy in various applications, including smart metering systems. Smart meters are essential components of modern energy grids, providing real-time…

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Secure multi-party computation for privacy-preserving federated learning – Complete Phd and Masters Thesis

Secure multi-party computation for privacy-preserving federated learning – Complete Phd and Masters Thesis

[ad_1] Introduction In recent years, federated learning has gained significant attention as a privacy-preserving technique for training machine learning models on distributed data sources. However, one of the key challenges in federated learning is ensuring…

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Quantum-resistant secure multi-party computation – Complete Phd and Masters Thesis

Quantum-resistant secure multi-party computation – Complete Phd and Masters Thesis

[ad_1] Introduction: Quantum computing has the potential to revolutionize the field of cryptography by breaking many of the commonly used encryption schemes. As quantum computers become more powerful, it is crucial to develop secure multi-party…

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Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) for privacy-preserving auctions – Complete Phd and Masters Thesis

Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) for privacy-preserving auctions – Complete Phd and Masters Thesis

[ad_1] Introduction Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) are powerful cryptographic tools that allow one party to prove to another party the knowledge of certain information without revealing the information itself. This technology has…

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Decentralized digital rights management using blockchain – Complete Phd and Masters Thesis

Decentralized digital rights management using blockchain – Complete Phd and Masters Thesis

[ad_1] Introduction As the digital world continues to expand rapidly, the issue of digital rights management (DRM) has become increasingly important. DRM refers to the technological protection and control measures implemented by content creators to…

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Quantum-inspired optimization for network resource allocation – Complete Phd and Masters Thesis

Quantum-inspired optimization for network resource allocation – Complete Phd and Masters Thesis

[ad_1] Introduction Quantum-inspired optimization has emerged as a promising approach for solving complex optimization problems in various domains. In the context of network resource allocation, the efficient utilization of resources is crucial for ensuring high…

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Multi-modal learning for visual-textual alignment – Complete Phd and Masters Thesis

Multi-modal learning for visual-textual alignment – Complete Phd and Masters Thesis

[ad_1] Introduction Multi-modal learning for visual-textual alignment is a rapidly growing research area that aims to bridge the gap between different modalities, such as images and text, in order to improve the performance of various…

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