A secure drone-to-drone communication and software defined drone network-enabled traffic monitoring system

Kumar, A. and Yadav, A.S. and Gill, S.S. and Pervaiz, H. and Ni, Q. and Buyya, R. (2022) A secure drone-to-drone communication and software defined drone network-enabled traffic monitoring system. Simulation Modelling Practice and Theory, 120: 102621. ISSN 1569-190X

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Abstract

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.