摘要
随着数字媒体技术的迅猛发展，用户隐私保护问题日益凸显，成为学术界与产业界共同关注的焦点。本研究旨在探讨数字媒体环境下用户隐私保护的关键技术及其应用，以应对日益复杂的隐私泄露风险。研究首先分析了当前数字媒体环境下的隐私威胁特征，包括数据过度采集、算法滥用及跨境数据流动等问题，并结合隐私保护技术的发展现状，提出了基于差分隐私、联邦学习和区块链的多层次隐私保护框架。通过构建实验平台，验证了该框架在数据共享场景中的有效性与可行性，结果表明其能够在保障数据效用的同时显著降低隐私泄露风险。此外，本研究创新性地引入用户行为偏好模型，优化了隐私保护策略的动态调整机制，提升了用户体验与安全性之间的平衡。最终结论显示，融合多技术路径的隐私保护方案能够有效应对数字媒体环境下的复杂挑战，为未来隐私保护技术的研究与实践提供了重要参考。
关键词：数字媒体隐私保护；差分隐私；联邦学习；区块链；用户行为偏好模型
Abstract
With the rapid development of digital media technology, user privacy protection has become increasingly prominent, drawing joint attention from both academia and industry. This study aims to explore key technologies and their applications for user privacy protection in digital media environments, addressing the growing complexity of privacy leakage risks. It begins by analyzing the characteristics of privacy threats in the current digital media landscape, including excessive data collection, algorithmic misuse, and cross-border data flows, while integrating these insights with the current state of privacy protection technology development. A multi-layered privacy protection fr amework based on differential privacy, federated learning, and blockchain is proposed. Through the construction of an experimental platform, the effectiveness and feasibility of this fr amework in data-sharing scenarios are validated, demonstrating its ability to significantly reduce privacy leakage risks while preserving data utility. Additionally, this research innovatively incorporates a user behavior preference model to optimize the dynamic adjustment mechanism of privacy protection strategies, enhancing the balance between user experience and security. The final conclusion indicates that a privacy protection solution combining multiple technical approaches can effectively address the complex challenges posed by digital media environments, providing significant reference for future research and practice in privacy protection technology.
Keywords：Digital Media Privacy Protection; Differential Privacy; Federated Learning; Blockchain; User Behavior Preference Model
目 录
摘要 I
Abstract II
一、绪论 1
(一) 数字媒体环境下的隐私保护背景与意义 1
(二) 用户隐私保护技术的研究现状分析 1
(三) 本文研究方法与技术路线 2
二、数字媒体用户隐私风险分析 2
(一) 数据泄露的主要形式与特征 2
(二) 隐私侵犯的技术手段剖析 3
(三) 用户行为数据的潜在风险评估 3
三、用户隐私保护关键技术研究 4
(一) 加密技术在隐私保护中的应用 4
(二) 匿名化技术的作用与实现方式 4
(三) 差分隐私技术的原理与实践 5
四、隐私保护技术的应用与优化策略 6
(一) 隐私保护技术在社交媒体中的应用 6
(二) 基于区块链的隐私保护方案设计 6
(三) 用户隐私保护的技术优化路径 7
结 论 8
参考文献 9
