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

Lim Wei Pin, Manmeet Mahinderjit Singh


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.


Biometrics; Cryptographic; Passwordless; Machine learning; Encryption

Full Text:




  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Bulletin of EEI Stats

Bulletin of Electrical Engineering and Informatics (BEEI)
ISSN: 2089-3191, e-ISSN: 2302-9285
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).