Journal article Open Access

Simulation of a Fine Dust Value-Based False Data Detection System to Improve Security In WSN-Based Air Purification IoT

Ye-lim Kang; Tae-ho Cho

Sponsor(s)
Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP)

Fine dust refers to harmful substances floating in the air. It is divided into PM 2.5 and PM 10, and has the characteristic that the particles are small enough to be invisible to the naked eye. When fine dust enters a room, it can enter the human body through the bronchi and cause lung or respiratory diseases. To solve the health problems caused by fine dust, research and development about various air purification systems are progressing. In this paper, we introduce a Wireless Sensor Networks (WSNs)-based Internet of Things (IoT) air purification system. This WSNs-based IoT air purification system refers to a system in which an IoT air purifier and a window are automatically controlled based on fine dust values detected by sensor nodes. Therefore, because it is important to maintain the integrity of the fine dust values, SSL/TLS, an encryption protocol, is applied to this system. However, the existing SSL/TLS has a problem in which, if an attacker attempts a false data injection attack, the symmetric key itself used to encrypt and decrypt the data is stolen, so it cannot be detected. To solve this problem, in this paper we propose a Discrete Event System Specification (DEVS) model based on Data Calibration that verifies whether the fine dust values detected by sensor nodes and an IoT air purifier is within a preset error range. If the fine dust value is not within the preset error range, it is detected as false data, filtered, and not stored in the database. Because this proposed scheme verifies the integrity of the fine dust values, it not only raises the accuracy of collected sensing data, but also prevents abnormal operation of an IoT air purifier and a window in advance. Therefore, the security of the WSNs-based IoT air purification system is improved. 

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