Essays about: "Homomorphic encryption"
Showing result 1 - 5 of 15 essays containing the words Homomorphic encryption.
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1. XZDDF Bootstrapping in Fully Homomorphic Encryption
University essay from Lunds universitet/Institutionen för elektro- och informationsteknikAbstract : Despite the vast research on the topic in recent years, fully homomorphic encryption schemes remain time-inefficient. The main bottleneck is the so-called bootstrapping, whose purpose is to reduce noise that has accumulated after having performed homomorphic operations on a ciphertext. READ MORE
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2. Preserving Privacy in Cloud Services by Using an Explainable Deep-Learning Model for Anomaly Detection
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : As cloud services become increasingly popular, ensuring their privacy and security has become a significant concern for users. Cloud computing involves Data Service Outsourcing and Computation Outsourcing, which require additional security considerations compared to traditional computing. READ MORE
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3. Homomorphic encryption
University essay from KTH/Matematik (Avd.)Abstract : The problem of constructing a secure encryption scheme that allows for computation on encrypted data was an open problem for more than 30 years. In 2009, Craig Gentry solved the problem, constructing the first fully homomorphic encryption (FHE) scheme. READ MORE
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4. Confidential Federated Learning with Homomorphic Encryption
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Federated Learning (FL), one variant of Machine Learning (ML) technology, has emerged as a prevalent method for multiple parties to collaboratively train ML models in a distributed manner with the help of a central server normally supplied by a Cloud Service Provider (CSP). Nevertheless, many existing vulnerabilities pose a threat to the advantages of FL and cause potential risks to data security and privacy, such as data leakage, misuse of the central server, or the threat of eavesdroppers illicitly seeking sensitive information. READ MORE
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5. Privacy Preserving Biometric Multi-factor Authentication
University essay from Lunds universitet/Institutionen för elektro- och informationsteknikAbstract : This thesis investigates the viability of using Fully Homomorphic Encryption and Machine Learning to construct a privacy-preserving biometric multi-factor authentication system. The system is based on the architecture described as ”Model K - Store distributed, compare distributed” in ISO/IEC 24745:2022 and uses the Torus Fully Homomorphic Encryption scheme proposed by Chillotti et al. READ MORE
