摘要
现有的匿名化方法多采用时空伪装技术,该技术计算负担重,LBS响应延迟时间长,导致LBS服务质量低.为此,提出了分解重构的匿名化方法,该方法首先对接收到的LBS查询集进行分组,形成满足匿名模型的等价类,然后对每个等价类根据不同的策略进行分解和重构,生成新的匿名查询集.此外,面向多种隐私需求,提出了一系列匿名模型,并进一步提出了基于分解重构技术的匿名模型的实现算法MBFAA.实验表明,提出的重构分解技术可以有效地实现各种匿名模型.
Most of the existing methods are realized by temporal and spatial cloaking techniques .However , these cloaking-based methods are disadvantageous due to their high computation loads and long response delays ,which lowers service quality . To address these problems , a novel technique , anatomy and reconstruction ,was proposed .This technique first partitions the LBS query set into several equivalence classes , making sure that each equivalence class satisfies the given anonymity constraints . T hen it reconstructs the LBS queries in each equivalence class according to the predefined strategies separately , and generates a new set of anonymous queries .Considering various privacy requirements ,a series of anonymity models were proposed , and a unified anonymization algorithm MBFAA was introduced to realize these models . Experimental results show that the proposed method can effectively implement all the anonymity models .
出处
《中国科学技术大学学报》
CAS
CSCD
北大核心
2014年第7期544-553,562,共11页
JUSTC
基金
国家基金项目(61170108
6110019)
浙江省自然科学基金(Y1100161
LQ13F020007)资助
