博论题目：大数据技术应用的安全风险及其多元治理研究
答辩人：员帅博
指导老师：刘大椿
答辩时间：2024年5月25日
目 录
导 论
0.1 选题背景和意义
0.1.1 选题背景
0.1.2 选题意义
0.2 国内外研究综述
0.2.1 国外研究综述
0.2.2 国内研究现状
0.2.3 研究评述
0.3 研究思路、方法和要点
0.3.1 研究思路
0.3.2 研究方法
0.3.3 可能的创新点和难点
第1章 大数据技术及其发展
1.1大数据技术的相关概念
1.1.1 大数据与大数据技术
1.1.2 大数据处理关键技术
1.2大数据技术的发展历程
1.2.1 大数据的发展阶段
1.2.2 大数据技术的发展历程
1.2.3 大数据在我国的发展
第2章 大数据技术的应用场景
2.1 大数据技术在产业方面的应用
2.1.1 在智慧消防领域
2.1.2 在新能源汽车领域
2.1.3 在精准农业领域
2.2 大数据技术在民生和社会服务方面的应用
2.2.1 民生方面
2.2.2 社会服务方面
2.3 大数据技术在安全保障领域的应用
2.3.1 安保方面
2.3.2 公安情报方面
2.4 我国的大数据技术交易
2.4.1 我国大数据技术交易的发展特点
2.4.2 我国大数据技术交易的主要类型
2.4.3 大数据交易的法治环境
第3章 大数据技术应用生命周期中的安全风险
3.1 大数据采集与安全风险
3.1.1 大数据采集的范围与策略
3.1.2 大数据采集的安全问题
3.1.3 对数据采集与隐私安全的反思
3.2 大数据存储与安全风险
3.2.1 大数据存储的特点分析
3.2.2 大数据存储的方式
3.2.3 大数据存储中的数据泄露风险分析
3.3 大数据处理与安全风险
3.3.1 大数据预处理
3.3.2 大数据处理分析
3.3.3 大数据处理中的安全风险分析
第4章 大数据技术社会应用的安全风险
4.1 数据造假与滥用带来的社会信任危机
4.1.1 数据造假
4.1.2 数据滥用
4.2 数据鸿沟与霸权带来的权利不平等
4.2.1 数据鸿沟
4.2.2 数据霸权
4.3 隐私侵犯与数据泄露带来的安全风险
4.3.1 隐私侵犯
4.3.2 数据泄露
第5章 大数据技术应用安全风险的多元治理
5.1 基于安全技术能力提升的风险防控策略
5.1.1 构建全方位的大数据安全技术能力体系
5.1.2 强化大数据安全人才技术水平提升
5.1.3 优化大数据安全技术投入的规模与结构
5.2 立足伦理道德建设的风险规制路径
5.2.1 厘清大数据伦理意识培育的基本原则
5.2.2 探索符合大数据时代特点的培育思路
5.2.3 树立大数据道德伦理的核心地位
5.3 发挥社会机制作用的风险治理方略
5.3.1 推动大数据行业自律机制的构建与完善
5.3.2 健全大数据行业奖惩机制以规范主体行为
5.3.3 打造社会各界多方协同的长效合作监督机制
5.4 构建以法治为基石的大数据安全防护机制
5.4.1 明晰大数据安全保障立法的总体目标
5.4.2 树立契合大数据时代特点的安全立法理念
5.4.3 构建兼顾统一与分散的大数据安全立法模式
结 语
参考文献
致 谢
摘 要
当下，大数据技术犹如一把双刃利剑，在挥舞间引领人类社会进入全新的篇章。它集数据采集、存储、管理、分析等多种功能于一身，点亮了政府治理、商业运营和科技创新的火花，使决策的准确性和效率得到了极大提升。然而，在这场大数据的风潮中，也隐匿着一系列不容忽视的危机。大数据应用所蕴含的各种风险正悄然侵蚀着个人权利，动摇着社会信任，重新塑造着文明进程的轨迹。从数据的收集、存储、处理直至应用，都隐藏着重要的安全隐患。我们正处于个人隐私与公共利益之间的紧张边缘，算法权力滥用与公众知情权的激烈博弈关头，以及数据寡头垄断与社会公平的悬殊鸿沟中。如果这些风险被放任继续蔓延，势必会削弱公民的基本权利，损害社会的公共利益。
面对大数据应用中隐现的安全风险，我们不能视而不见，任其泛滥蔓延。扭转这一困境的关键，在于建立起科学合理、多元全面的治理体系，以使大数据技术在社会中的应用回归正道。本研究旨在全面审视大数据技术中潜在的危机，并深入分析其背后的伦理危机，以此为基础，积极探索治理之策。本文在文献理论基础上，结合智慧消防、医疗健康、交通、生态等案例分析，进行交叉研究，旨在构建多学科融合的大数据技术多元治理体系。全文共分为六个部分，涵盖了大数据技术及其发展历程、应用场景、安全风险及多元治理措施。
导论介绍了本文选题的依据、国内外研究概况、研究思路与方法、拟创新之处和难点。尤其对国内与国际上对大数据技术的实际应用、价值与社会伦理层面进行多角度梳理，在此基础上将前沿的大数据技术应用的安全风险与多元治理结合起来，试图构建一个多学科融合的大数据技术治理的模型。
第一章厘清大数据技术的相关概念与发展历程。全方位地探究大数据的定义、特性和范畴，对大数据、大数据技术、大数据处理关键技术进行辨析，分析大数据技术在处理能力、数据量、多样性以及数据价值等方面与传统数据集的显著差异，细腻地勾勒大数据技术在信息时代舞台上的发展历程以及在我国的发展态势，以便更好地把握其独特性。
第二章审视大数据技术的三大应用场景，结合案例生动地展现其跨领域的变革性影响。在产业方面，大数据技术的应用范围广泛，涵盖了智慧消防、新能源汽车和精准农业等领域；在民生和社会服务方面，大数据技术适用于改善民生和提供社会服务；在安全保障方面，尤其是安保和公安情报中致力于提升办案效率。最后，对我国的大数据技术交易进行了分析，包括其发展特点、主要类型以及法治环境，为深入理解大数据技术在国内应用和发展的背景提供重要参考。
第三章深入剖析大数据技术应用中的基本环节及其潜在的安全风险。大数据的生命周期中，每个阶段都面临着特定的安全威胁，这些威胁可能影响到整个系统的安全性和数据的可靠性。为了全面透彻地探析大数据技术在核心环节所面临的安全挑战，从数据的萌芽——采集过程开始，审视防御措施，以确保数据在生成时的安全传输和保护；随后，关注数据的静态存在形态——存储阶段，探讨如何避免数据泄露和丢失，确保备份和恢复流程的健壮性；在数据被激活——处理阶段，评估如何确保处理活动的安全性。
第四章针对性地聚焦大数据技术应用中突出的三大数据安全风险。在数据造假与数据滥用方面，出现了严重的社会信任危机；数据鸿沟和数据霸权造成了权利不平等的现象，进一步加剧了社会的分化和不公；隐私侵犯和数据泄露也成为了风险的焦点，算法的不透明性则可能导致个人隐私权的损害，数据主权的流失也将加剧公民的信息安全困境。这些问题的存在，凸显了大数据技术应用中的挑战与问题，需要采取有效措施加以解决。
第五章系统地提出多元治理下的大数据技术应用安全风险的治理措施，旨在构建一个更安全、透明和负责任的大数据生态环境。首先，提升规避风险的大数据安全技术的策略，包括加强大数据安全技术能力体系建设、提高相关人员的网络安全技术水平和加强对大数据防护安全技术的投入。其次，培育大数据伦理意识和责任意识的重要性，包括明确伦理意识培育的主要原则和基本思路，以及开展大数据伦理道德教育的必要性。然后，强化大数据安全的社会机制，建设行业自律机制、建立行业奖惩机制、建立长效合作监督机制。最后，完善大数据安全的法律法规的措施，明确大数据安全保障的立法目的、秉承立法理念和完善立法模式。这些策略为多元治理下的大数据技术应用安全提供重要的借鉴，以期提高社会各界对数据安全问题的警觉性，为建立健全的数据安全保护机制提供理论依据。
综上所述，本研究立足当下大数据技术发展的迫切现实需求，针对其应用中存在的诸多安全风险与伦理困境，全面深入地进行分析研究，进而“对症下药”，提出细致的解决方案。不仅深入剖析了各个应用环节的风险点，更是积极地构建起培育伦理意识、完善法规体系和提升技术水平的管理框架。这一系列措施旨在为相关决策部门和企业制定大数据技术的监管与自律机制提供可靠的决策依据，为大数据技术的良性发展指明方向。
关键词：大数据；技术应用；安全风险；多元治理
Abstract
Currently, big data technology is like a double-edged sword, leading human society into a new era while swinging. It integrates various functions such as data collection, storage, management, and analysis, sparking sparks in government governance, business operations, and technological innovation, greatly enhancing the accuracy and efficiency of decision-making. However, within this wave of big data, there are also a series of crises that cannot be ignored. Various risks inherent in the application of big data are quietly eroding individual rights, shaking social trust, and reshaping the trajectory of civilization. From data collection, storage, processing to application, there are significant security risks hidden in each aspect. We are on the edge between personal privacy and public interest, in the intense game between algorithmic abuse of power and the public's right to know, and in the stark gap between data oligopoly and social equity. If these risks are allowed to continue to spread, they will undoubtedly weaken citizens' basic rights and harm the public interest.
Facing the security risks hidden in the application of big data, we cannot turn a blind eye and let them spread unchecked. The key to reversing this dilemma lies in establishing a scientific, rational, and comprehensive governance system to guide the application of big data technology back on track in society. This study aims to comprehensively examine the potential crises in big data technology and deeply analyze the ethical dilemmas behind them, actively exploring governance strategies based on this foundation. In the surging tide of data, we must adhere to principles and innovate courageously; in the vortex of algorithms, we must not forget the light and move forward steadfastly. This thesis is divided into six parts, covering the technology and development process of big data, application scenarios, security risks, and multi-dimensional governance measures.
The introduction introduces the basis for the selection of the topic of this paper, the overview of domestic and international research, research ideas and methods, proposed innovations and difficulties. In particular, the practical application, value and social ethical dimensions of big data technology are sorted out from multiple perspectives at home and abroad, on the basis of which the security risks of cutting-edge big data technology applications are combined with multifaceted governance, in an attempt to construct a model for big data technology with multidisciplinary integration.
Chapter 1 clarifies the relevant concepts and development process of big data technology. We comprehensively explore the definition, characteristics, and scope of big data, analyzes the differences between big data, big data technology, and key technologies for big data processing, and delicately outlines the development process of big data technology on the stage of the information age and its development trend in China to better grasp its uniqueness.
Chapter 2 examines the three major application scenarios of big data technology, vividly demonstrating its transformative impact across fields with case studies. In the industrial field, the application scope of big data technology is extensive, covering areas such as smart firefighting, new energy vehicles, and precision agriculture. In the field of people's livelihood and social services, big data technology is suitable for improving people's livelihood and providing social services. In terms of security guarantee, especially in security and public security intelligence, it is committed to improving case handling efficiency. Finally, an analysis of China's big data technology transactions, including their development characteristics, main types, and legal environment, provides important references for understanding the background of domestic applications and development of big data technology.
Chapter 3 thoroughly analyzes the four basic links and their potential security risks in the application of big data technology. In the life cycle of big data, each stage faces specific security threats, which may affect the overall security of the system and the reliability of the data. In order to comprehensively analyze the security challenges faced by big data technology in core links, we start from the collection process of data, examine defense measures to ensure the secure transmission and protection of data at the time of generation; then, focus on the storage stage, discussing how to avoid data leakage and loss and ensure the robustness of backup and recovery processes; in the processing stage, we evaluate how to ensure the security of processing activities.
Chapter 4 focuses on three prominent data security risks in the application of big data technology. In terms of data fraud and misuse, a serious social trust crisis has emerged; data divide and data hegemony have caused unequal rights, further exacerbating social differentiation and injustice; privacy infringement and data leakage have also become the focus of security risks, while algorithmic opacity may lead to personal privacy violations, and the loss of data sovereignty will exacerbate citizens' information security dilemma. The existence of these problems highlights the challenges and problems in the application of big data technology, which need to be effectively addressed.
Chapter 5 systematically proposes governance measures for the security risks of big data technology applications under multi-dimensional governance, aiming to build a safer, more transparent, and responsible big data ecosystem. Firstly, the strategy to enhance the security of big data technology to avoid risks is proposed, including strengthening the construction of the big data security technology capability system, improving the network security technology level of relevant personnel, and strengthening investment in big data protection security technology. Secondly, the importance of nurturing ethical awareness and responsibility in big data is emphasized, including clarifying the main principles and basic ideas of ethical awareness cultivation and the necessity of conducting ethics and morality education in big data. Then, the need to strengthen the social mechanisms of big data security is discussed, including the establishment of industry self-discipline mechanisms, the establishment of industry reward and punishment mechanisms, and the establishment of long-term cooperative supervision mechanisms. Finally, measures to improve the laws and regulations of big data security are proposed, including clarifying the legislative purpose of big data security protection, adhering to the legislative concept of big data security, and improving the legislative mode under the guidance of legislative concepts. These strategies provide important references for the security of big data technology applications under multi-dimensional governance, aiming to raise the awareness of various sectors of society to data security issues and provide theoretical basis for establishing a sound data security protection mechanism.
In conclusion, this study is based on the urgent practical needs of the current development of big data technology, and aims to comprehensively and deeply analyze the many security risks and ethical dilemmas existing in its application, and then propose detailed solutions. We not only deeply analyze the risk points of each application link but also actively builds a management framework for nurturing ethical awareness, improving regulatory systems, and enhancing technical levels. These measures are intended to provide reliable decision-making basis for relevant decision-making departments and enterprises to formulate supervision and self-discipline mechanisms for big data technology, and to provide guidance for the healthy development of big data technology.
Keywords: Big data；Technology Application; Security risks; Multi-dimensional Governance
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