Secure Cloud Connected Indoor Hydroponic System via Multi-factor Authentication

Now-a-days, the hydroponic farming system with the Internet of Things (IoT) technology is increasingly becoming a trend for researchers to produce a more capable farming device or remote monitoring system. However, this intelligent system is not controlled securely and will be dangerous when system hacking occurs. Therefore, developing a secure indoor hydroponic monitoring device with multi-factor authentication (MFA) method is proposed. The research aims to develop a secure cloud-connected indoor hydroponic system via multi-factor authentication on the ThingsSentral IoT platform with an MFA technique. The developed system comprises an iPhone Operating System (iOS), an Arduino node microcontroller unit and a ThingsSentral web IoT platform. A security software application on iOS phones with MFA techniques is built to authenticate devices before communicating with ThingsSentral.io. Token authentication between ThingsSentral.io and the security software application must be done before the hydroponic monitoring device can send and receive data. An indoor hydroponic monitoring system device with MFA security technique has been successfully produced from the study. An MFA security technique for iOS apps has also been successfully developed. In conclusion, using the MFA technique, this research successfully develops a high-security control and communication system between the field device and the IoT platform. Although the MFA security system developed for this IoT platform has several steps that need to be done before data can be sent to the cloud database, the users themselves can allow or prohibit a device from operating. Besides, users can also control and monitor the security between the device and the IoT platform when they operate.

@article{Rahimi2022,
  title     = {Secure Cloud Connected Indoor Hydroponic System via Multi-factor Authentication},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {9},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {Mohamad Khairul Hafizi Rahimi and Mohamad Hanif Md Saad and Aini Hussain and Nurul Maisarah Hamdan},
  doi       = {10.14569/IJACSA.2022.0130925},
  url       = {https://doi.org/10.14569/IJACSA.2022.0130925}
}