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论文范文
1. Introduction With the development and construction of novel learning applications for smart campus, smart devices and services, smart meters, smart terminals, and the like are widely applied to offer real-time learning feedback to students through continuously monitoring and analyzing the status and activities of students with various devices and platforms. As a large number of smart meters and intelligence appliances are accessed, incorporating various technologies and enabling world-changing learning, the network border further extends to the user side. Security risks on the user side for smart campus will become more and more prominent. Data privacy issues, especially location privacy protection and the quality of service, must be considered [1]. Users’ location privacy threats refer to the risks that an attacker can obtain unauthorized access to raw location data by locating a transmitting device and identifying the subject (person) using it. Examples of such risks include spamming users with unwanted advertisements, drawing sensitive inferences from victims’ visits to various locations (e.g., students and teachers’ offices), and learning sensitive information about them (identity, religious and political affiliations, etc.). Hence, location privacy protection for smart campus is becoming a critical issue [2]. However, location information is consistently sent to service providers without protection when users query LBSs, allowing location providers to collect location information from all users. The collected location information may expose users to customized advertisement or even be sold to third parties. A worse scenario is location information may be leaked to adversaries with criminal intents. Therefore, many researchers focus on creating location protection algorithms to protect the location privacy of users [3]. The European Union’s Information Protection Supervision Organization recently said that high-tech equipment such as smart meters that monitor household energy consumption will pose a huge threat to personal privacy. Smart meters may track personal information, and the vast amounts of information collected can have serious consequences for consumers. With the popularization of mobile devices and location technology, location-based services (LBSs) are widely used in real life, which refers to the user accesses to its designated location information query and entertainment services through the mobile device [4]. However, the location-based service provider (LSP) may also collect and abuse user’s service information while providing the convenient LBS for the user, to illegally obtain the user’s confidential information. The location privacy protection in LBS has attracted the extensive attention of researchers [5–8]. In view of the popularization of mobile positioning devices, if these novel learning applications are used in smart campus, the combination of location information and services at different moments in personal privacy may reveal sensitive information such as the user’s behavior habits and work nature. For example, if a mobile user is collected near a hospital, the user may be presumed to have any disease or health condition. If the user’s starting location and ending location are analyzed since the last few days, the user’s home address or work unit, the nature of work, and so on can be speculated. Therefore, the location data of mobile object brings convenience to people and brings about the threat of revealing privacy, which may contain other sensitive information such as home address, personal preference, personality habit, health status, working property, personal income, etc. If this information falls into the hands of normal institutions, it is a tool for information protection, if it falls into the hands of illegal institutions, it will be the weapon of innocent destruction. What we can do is to seek transparency in the use of personal information and to protect user’s location privacy not to be exploited by unscrupulous businesses and illegal agencies. 
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