摘要
2层无线传感器网络由于具有寿命长和易扩展的特点,已经成为当前的研究热点.Top-k查询是一种重要的查询类型,但是大多数的Top-k查询不能执行精确查询任务.提出了一种精确的Top-k查询算法PI-TQ(privacy-preserving integrity-verification Top-kquery),同时提供了隐私保护和完整性验证功能.算法采用2次查询方法以减少数据通信量,利用基于干扰数的扰动算法实现隐私保护,并采用概率空间邻居验证模式实现完整性验证.仿真结果表明,PI-TQ算法与同类算法相比较,可以明显减少查询的通信量和计算代价,同时保证查询结果的正确性、隐私性和完整性.
The two-tiered wireless sensor networks have become the research hotspot because of its scalability and long lifetime. Top-k query is an important query type but most Top-k query technologies cannot perform precise query. :A Top-k query asks for data items whose numeric attributes are among the k highest, where k is an application-dependent parameter. The privacy preservation is important for Top-k query in a hostile environment because sensitive information may leak from compromised nodes. The integrity and authenticity of the Top-k query results should be verified because the adversary can instruct a compromised master node to delete or modify data in response to Top-k queries. This paper presents a precise query algorithm called PI-TQ (privacy- preserving integrity-verification Top-k query) which provides both privacy preservation and integrity verification. The algorithm uses a two-step query method to reduce the communication traffic between nodes and sinks. To ensure the privacy and correctness of the query results, the perturbation algorithm is utilized to protect the privacy of sensitive data. The neighbor verification method achieves integrity verification by using probability space. The simulation results show that PI-TQ algorithm can greatly reduce the computational cost and traffic consumption compared with other algorithms. It can also guarantee accuracy, privacy and integrity of the query results.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2014年第12期2585-2592,共8页
Journal of Computer Research and Development
基金
国家自然科学基金项目(61202353
61272084
61300240)
江苏省高校自然科学研究项目(12KJB520008)
江苏省普通高校研究生科研创新计划基金项目(CXLX13_464)
关键词
2层无线传感器网络
TOP-K查询
隐私保护
完整性验证
数据扰动
two-tiered wireless sensor, networks
Top-k query
privacy preserving
integrityverification
data perturbation