User authentication using gait and enhanced attribute-based encryption: a case of smart home

Lim Wei Pin, Manmeet Mahinderjit Singh
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Abstract

With the increasing popularity of the internet of things (IoT) application such as smart home, more data is being collected, and subsequently, concerns about preserving the privacy and confidentiality of these data are growing. When intruders attack and get control of smart home devices, privacy is compromised. Attribute-based encryption (ABE) is a new technique proposed to solve the data privacy issue in smart homes. However, ABE involves high computational cost, and the length of its ciphertext/private key increases linearly with the number of attributes, thus limiting the usage of ABE. This study proposes an enhanced ABE that utilises gait profile. By combining lesser number of attributes and generating a profiling attribute that utilises gait, the proposed technique solves two issues: computational cost and one-to-one encryption. Based on experiment conducted, computational time has been reduced by 55.27% with nine static attributes and one profile attribute. Thus, enhanced ABE is better in terms of computational time.
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利用步态和增强型属性加密进行用户身份验证:智能家居案例
随着智能家居等物联网(IoT)应用的日益普及,越来越多的数据被收集起来,随之而来的是对保护这些数据的隐私和保密性的担忧。当入侵者攻击并控制智能家居设备时,隐私就会被泄露。基于属性的加密(ABE)是一种解决智能家居数据隐私问题的新技术。然而,ABE 的计算成本较高,而且其密文/私钥的长度随属性数量的增加而线性增加,因此限制了 ABE 的使用。本研究提出了一种利用步态特征的增强型 ABE。通过组合较少数量的属性并生成一个利用步态的剖析属性,所提出的技术解决了两个问题:计算成本和一对一加密。根据实验结果,使用九个静态属性和一个轮廓属性,计算时间减少了 55.27%。因此,增强型 ABE 在计算时间方面更胜一筹。
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