Detection of False Report Injection At Wsns Based on Data Calibration in Iot Environment
Ye-lim Kang1, Tae-ho Cho2
1Ye-lim Kang, Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea.
2Tae-ho Cho*, Department of Computer Science and Engineering, Sungkyunkwan University, Suwon, Republic of Korea.

Manuscript received on November 15, 2019. | Revised Manuscript received on November 28, 2019. | Manuscript published on 30 November, 2019. | PP: 8956-8960 | Volume-8 Issue-4, November 2019. | Retrieval Number: D9746118419/2019©BEIESP | DOI: 10.35940/ijrte.D9746.118419

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Abstract: Unlike ordinary dust, fine dust has a small particle size and is thus not well-filtered out of the human nose or bronchus. It accumulates in the human body where it can generate various respiratory and bronchial illnesses. If this fine dust is introduced into a room from the outside, the indoor air is worsened which has negative effects on the health of the people there. The continuous management of indoor air through air purification is necessary to protect the health of students, office workers, and others who spend most of the day indoors. Various air purification systems exist for this purpose, and research and development are actively progressing. This paper discusses an indoor air purification system that uses Internet of Things (IoT) based on Wireless Sensor Networks (WSNs). In such a system, false reports are generated when the number of sensor nodes compromised by an attacker exceeds the security threshold. The WSNs security protocol, Interleaved Hop-by-hop Authentication (IHA), cannot defend against such false reports, resulting in abnormal behavior of the IoT air cleaner. Therefore, a false report detection scheme that uses sensing data is proposed in this paper. When fine dust occurs, the WSNs and IoT air cleaner sense fine dust at the same time. The IoT air cleaner, which has normally received the WSNs event report, calculates the average and the deviation about the cumulative fine dust sensing data values of the WSNs and the IoT. Then, it compares the deviation for the current event with the deviation for the previous event to calculate the variation of deviation. If the variation of deviation is within a predetermined error range, it is determined that a normal event occurs. Otherwise, it is determined that the false report injection attack occurs and it is prevented from running abnormal behavior of it. In conclusion, this scheme not only improves security by preventing the IoT air cleaner from running abnormally, but also contributes to improved energy efficiency in the WSNs.
Keywords: Wireless Sensor Networks, Internet of Things, Interleaved Hop-by-hop Authentication, Fine dust, Security Protocol, False report injection attack
Scope of the Article: Internet of Things.