Using an Efficient Detection Method to Prevent Personal Data Leakage for Web-Based Smart City Platforms

Abstract

Many Internet of Things and information exchange technologies bring convenience, cost-efficiency, and sustainability to smart city solutions. These changes have improved our day-to-day quality of life, with impacts on: (a) lifestyle (e.g., automation and robotic reaction), (b) infrastructure (efficient energy consumption), and (c) data-driven management (data sensing, collection, and investigation). It is common to integrate Web-based interfaces and such solutions for developing platforms. When software and hardware components store, retrieve, and transfer such information, people may suffer from personal data leakage. This paper introduces a privacy information detection method, using a data weighting mechanism to save time and cost in finding personal information leaks over Web services. According to an initial evaluation, the proposed method can reduce time by 62.19% when processing 8,000 crawled files, and roll-back verification shows that it maintains 90.08% accuracy for finding marked content.