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A Trusted Security Key Management Server in LoRaWAN: Modelling and Analysis.

Authors :
Ntshabele, Koketso
Isong, Bassey
Gasela, Naison
Abu-Mahfouz, Adnan M.
Source :
Journal of Sensor & Actuator Networks; Sep2022, Vol. 11 Issue 3, pN.PAG-N.PAG, 23p
Publication Year :
2022

Abstract

The traditional Long-Range Wide-Area Network (LoRaWAN) uses an Advanced Encryption Standard (AES) 128 bit symmetric key to secure entities and data against several attacks. However, due to the existence of heterogeneous applications, designing a globally accepted and resilient LoRaWAN security model is challenging. Although several security models to maximize the security efficiency in LoRaWAN exist using the trusted key server to securely manage the keys, designing an optimum LoRaWAN security model is yet to be fully realized. Therefore, in this paper, we proposed two LoRaWAN security algorithms, A and B, for a trusted key management server (TKMS) to securely manage and distribute the keys amongst the entities. Algorithm B is an enhanced version of Algorithm A, which utilizes the security shortcomings of Algorithm A. We employed two formal analysis methods in the modelling, results analysis, and verification. The Scyther security verification tool was used for algorithm modelling and analysis against all possible attacks, while BAN logic was used to prove the logical correctness of the proposed algorithms. The results indicate that BAN logic feasibly proves the model logic correctness and the security claims employed in Scyther are reliable metrics for assessing the algorithms' security efficiency. The security claims proved that the security algorithm is more secure and reliable as no attacks were detected across all entities in the enhanced-Algorithm B, unlike in Algorithm A. Moreover, the application of hashing minimizes computation cost and time for authentication and message integrity as compared to symmetric and asymmetric encryption. However, the proposed algorithm is yet to be verified as completely lightweight. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22242708
Volume :
11
Issue :
3
Database :
Complementary Index
Journal :
Journal of Sensor & Actuator Networks
Publication Type :
Academic Journal
Accession number :
159334126
Full Text :
https://doi.org/10.3390/jsan11030052