大数据“杀熟”的消费者信息安全问题研究——以滴滴打车为例

Research on Consumer Information Security Issues in Big Data-Based “Price Discrimination”—A Case Study of Didi Chuxing

摘要: 在信息技术迅猛发展的背景下，大数据“杀熟”现象和个人隐私安全问题备受关注。作为新时代的关键资源，数据已成为企业精准营销与动态定价的核心工具。尤其在共享经济平台如滴滴打车中，企业通过获取和分析用户的行为与特征数据，制定个性化的定价策略，虽然提升了服务体验，却也引发了数据滥用和“杀熟”的争议，消费者的公平感与隐私安全受到威胁。本文通过机器学习算法，以滴滴打车平台为例，研究含有特定特征的消费者是否更易受到大数据“杀熟”的影响。通过预测结果分析各特征变量的重要性，提出了对敏感数据加密保护的措施。研究不仅揭示了大数据应用中的潜在风险，也为消费者隐私保护与信息安全提出了实用建议，呼吁企业在数据使用中应平衡个性化服务与用户权益的保护。

Abstract: Amid the rapid development of information technology, the phenomena of big data-based “price discrimination” and personal privacy security have garnered significant attention. As a key resource in the new era, data has become a core tool for enterprises in precision marketing and dynamic pricing. Especially on shared economy platforms like Didi Chuxing, companies leverage user behavior and feature data to develop personalized pricing strategies. While this approach enhances service experiences, it also raises concerns about data misuse and “price discrimination”, threatening consumers’ sense of fairness and privacy security. This study, using machine learning algorithms and taking Didi Chuxing as a case study, investigates whether consumers with specific characteristics are more susceptible to big data-based “price discrimination”. By analyzing the importance of various feature variables through prediction results, the study proposes measures for the encryption and protection of sensitive data. The research not only reveals potential risks in big data applications but also offers practical recommendations for consumer privacy protection and information security, urging companies to balance personalized services with the protection of user rights in data usage.