Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/142217
Title: A malicious behavior awareness and defense countermeasure based on LoRaWAN protocol
Authors: Gao, Shu-Yang
Li, Xiao-Hong
Ma, Maode
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2019
Source: Gao, S.-Y., Li, X.-H., & Ma, M. (2019). A malicious behavior awareness and defense countermeasure based on LoRaWAN protocol. Sensors, 19(23), 5122-. doi:10.3390/s19235122
Journal: Sensors
Abstract: Low power wide area network (LoRaWAN) protocol has been widely used in various fields. With its rapid development, security issues about the awareness and defense against malicious events in the Internet of Things must be taken seriously. Eavesdroppers can exploit the shortcomings of the specification and the limited consumption performance of devices to carry out security attacks such as replay attacks. In the process of the over-the-air-activation (OTAA) for LoRa nodes, attackers can modify the data because the data is transmitted in plain text. If the user's root key is leaked, the wireless sensor network will not be able to prevent malicious nodes from joining the network. To solve this security flaw in LoRaWAN, we propose a countermeasure called Secure-Packet-Transmission scheme (SPT) which works based on the LoRaWAN standard v1.1 to prevent replay attacks when an attacker has obtained the root key. The proposed scheme redefines the format of join-request packet, add the new One Time Password (OTP) encrypted method and changes the transmission strategy in OTAA between LoRa nodes and network server. The security evaluation by using the Burrows-Abadi-Needham logic (BAN Logic) and the Scyther shows that the security goal can be achieved. This paper also conducts extensive experiments by simulations and a testbed to perform feasibility and performance analysis. All results demonstrate that SPT is lightweight, efficient and able to defend against malicious behavior.
URI: https://hdl.handle.net/10356/142217
ISSN: 1424-8220
DOI: 10.3390/s19235122
Rights: © 2019 The Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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