基于安全压缩感知的大数据隐私保护

Big data privacy protection based on secure compressive sensing

当前的数据"大爆炸"主要受万物互联的驱动,服务于人类衣食住行的各类物联网感知设备时刻在捕获个人隐私数据,然而,这些隐私数据已成为网络攻击的重点目标。分析了资源受限的物联网应用中的数据安全问题,介绍了基于压缩感知理论的隐私保护技术——安全压缩感知,提出了相应的大数据采集方案,并且通过安全性理论和实验分析给出了结论性的呼吁:将安全压缩感知作为一种感知层内置的轻量级加密机制,以近乎零的成本为数据提供第一层安全防护。

The current"big bang"of data is mainly driven by interconnection of all things.Various types of IoT sensing devices serving in daily life are constantly capturing personal privacy data.However,these privacy data have become the key targets of network attacks.Data security issues in the resource-constrained IoT applications were analyzed,a novel privacy protection technique based on compressive sensing theory was introduced,which is called secure compressed sensing,and a corresponding big data collection scheme was proposed.As demonstrated by the theoretical and experimental security analysis,there is a conclusive appeal for that secure compressive sensing can be used as a lightweight encryption mechanism which is built into the perception layer to provide first-level security protection for data at almost zero cost.