Improving Scalability for RFID Privacy Protection Using Parallelism

Seong-pyo Hong, Moon-Su Jung, Il-Yong Chung
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Abstract

In the ubiquitous environment of the next generation, RFID is predicted to occupy an important technical location and also expected to apply to various fields. However, the properties of tags in itself which is the core of RFID have a dysfunction like an invasion of privacy for user. An existing cryptanalytic protection scheme of the information leakage has a difficult problem to apply to RFID tags for privacy protection. We applied Ohkubo scheme to the protection of the tag's information efficiently in the RFID system environment using low-cost tags. But, this method has all information of tags to identify tag's ID and then performs the process of identification in sequence in the Back-end server. These processes have lots of computations so that it has problems about scalability. In this paper, we are based on Ohkubo scheme to solve problems, and then analyze the parallelism with the Hellman’s tradeoff method and divide it into nodes in parallel. As a result, we can reduce the computing complexity. So, we show the results to be enhanced the scalability.
利用并行性提高RFID隐私保护的可扩展性
在下一代无处不在的环境中,预计RFID将占据重要的技术地位,也有望应用于各个领域。然而,作为RFID技术核心的标签本身的属性却存在着侵犯用户隐私等功能障碍。现有的信息泄露密码分析保护方案难以应用于RFID标签的隐私保护。在使用低成本标签的RFID系统环境中,我们将大久保方案有效地保护标签的信息。但是,该方法具有标签的所有信息,用于识别标签的ID,然后在后端服务器中依次执行识别过程。这些进程有大量的计算,因此存在可伸缩性问题。在本文中,我们基于Ohkubo方案来解决问题,然后用Hellman的权衡方法分析并行性,并将其并行划分为节点。因此,我们可以降低计算复杂度。因此,我们展示了增强可伸缩性的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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