In Body Area Networks (BANs), big data collected by wearable sensors usually contain sensitive information, which is compulsory to be appropriately protected. Previous methods neglected privacy protection issue, leading to privacy exposure. In this paper, a differential privacy protection scheme for big data in body sensor network is developed. Compared with previous methods, this scheme will provide privacy protection with higher availability and reliability. We introduce the concept of dynamic noise thresholds, which makes our scheme more suitable to process big data. Experimental results demonstrate that, even when the attacker has full background knowledge, the proposed scheme can still provide enough interference to big sensitive data so as to preserve the privacy.
Heteroepitaxy SiGe on Si by liquid phase epitaxy (LPE) is a potential material for photovoltaic application. The Si0.05Ge0.95 solar cell with an energy gap of 0.72 eV can lead to a 7 percentage point increase in the Si-based multibandgap system or any multi-bandgap system that contains Si as the 1.
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