Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - A secure drone-to-drone communication and software defined drone network-enabled traffic monitoring system
AU - Kumar, A.
AU - Yadav, A.S.
AU - Gill, S.S.
AU - Pervaiz, H.
AU - Ni, Q.
AU - Buyya, R.
N1 - This is the author’s version of a work that was accepted for publication in Simulation Modelling Practice and Theory. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Simulation Modelling Practice and Theory, 120, 2022 DOI: 10.1016/j.simpat.2022/102621
PY - 2022/11/30
Y1 - 2022/11/30
N2 - This paper proposes a novel lightweight security-enabled distributed software-defined drone network (SDDN) for traffic monitoring. Security of drone/Unmanned Aerial Vehicles (UAV) communication and data exchange is ensured through lightweight key generation and encryption/decryption algorithm. A hybrid (static and dynamic) OpenMP/MPI-based distributed processing is used to compute the security primitives for drone-to-drone communication. The proposed approach is more reliable, scalable and interoperable compared to other centralized logical control and incorporating network programming methods. Additionally, the use of cryptographic primitives and protocols make it more secure against attacks. A comparative analysis of proposed lightweight key generation and encryption/decryption algorithms with state-of-the-art algorithms shows that both proposed algorithms require fewer Gate Equivalents (GEs), and it varies from 18.4k to 29.6k. In terms of performance, both algorithms’ computational delay varies from 1.5 to 2 s. Jitter lies between 0.7 msec and 2 msec. The proposed algorithms are found to have communicational costs varying with 0.4 and 0.7 times of input in bytes with a base value of 1.4 and 1.25. Further, energy consumption is varying with 0.4 and 0.7 times of input in bytes with a base value of 0.3 and 0.25. Security interruption probability variation analysis show that the proposed security algorithms are better compared to state-of-the-art approaches. Further, security analysis of both algorithms (using a statistical and formal model) shows that the proposed system is protected against various attacks.
AB - This paper proposes a novel lightweight security-enabled distributed software-defined drone network (SDDN) for traffic monitoring. Security of drone/Unmanned Aerial Vehicles (UAV) communication and data exchange is ensured through lightweight key generation and encryption/decryption algorithm. A hybrid (static and dynamic) OpenMP/MPI-based distributed processing is used to compute the security primitives for drone-to-drone communication. The proposed approach is more reliable, scalable and interoperable compared to other centralized logical control and incorporating network programming methods. Additionally, the use of cryptographic primitives and protocols make it more secure against attacks. A comparative analysis of proposed lightweight key generation and encryption/decryption algorithms with state-of-the-art algorithms shows that both proposed algorithms require fewer Gate Equivalents (GEs), and it varies from 18.4k to 29.6k. In terms of performance, both algorithms’ computational delay varies from 1.5 to 2 s. Jitter lies between 0.7 msec and 2 msec. The proposed algorithms are found to have communicational costs varying with 0.4 and 0.7 times of input in bytes with a base value of 1.4 and 1.25. Further, energy consumption is varying with 0.4 and 0.7 times of input in bytes with a base value of 0.3 and 0.25. Security interruption probability variation analysis show that the proposed security algorithms are better compared to state-of-the-art approaches. Further, security analysis of both algorithms (using a statistical and formal model) shows that the proposed system is protected against various attacks.
KW - Security analysis
KW - Lightweight security mechanism
KW - Distributed computing
KW - Message passing interface (MPI)
KW - Unmanned autonomous vehicles (UAV)
U2 - 10.1016/j.simpat.2022.102621
DO - 10.1016/j.simpat.2022.102621
M3 - Journal article
VL - 120
JO - Simulation Modelling Practice and Theory
JF - Simulation Modelling Practice and Theory
SN - 1569-190X
M1 - 102621
ER -