Blockchain and Deep Learning Empowered Secure Data Sharing Framework for Softwarized UAVs

Kumar, P and Kumar, Randhir and Kumar, Abhinav and Franklin, Antony and Jolfaei, Alireza (2022) Blockchain and Deep Learning Empowered Secure Data Sharing Framework for Softwarized UAVs. In: 2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022, 16 May 2022 through 20 May 2022, Seoul.

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Softwarized Unmanned Aerial Vehicles (UAVs) use network programmability concept of Software-Defined Network (SDN) to separate the hardware control layer from the data layer via OpenFlow protocols. The softwarized UAV enable ubiquitous connection, as well as a flexible, cost-effective, and improved method for upgrading all network services without shutting down the entire system. However, the connectivity of UAVs with OpenFlow switches and their heavy reliance on unsecured communication protocols makes the entire network vulnerable. This is a critical concern, particularly in combat surveillance, where eavesdropping, adding, changing, or deleting messages during communications between deployed UAVs and SDN controller is a possible threat. To mitigate the aforementioned issues, this paper presents a novel secure data sharing framework for softwarized UAV environments that incorporates blockchain and Deep Learning (DL). First we present a blockchain-based technique to reg-ister, verify and thereafter validate the communication entities in softwarized UAV environment using smart contract-based Proof-of-Authentication (PoA) consensus mechanism. Additionally, a new deep neural network architecture-based flow analyzer is designed to detect illegitimate transactions. The latter combines a Stacked Contractive Sparse AutoEncoder with Attention-based Long Short-term Memory Neural Network (SCSAE-ALSTM) to improve intrusion detection process. The effectiveness of our framework over several standard baseline methodologies is demonstrated by security analysis and experimental findings. © 2022 IEEE.

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IITH Creators:
IITH CreatorsORCiD
Kumar, Abhinav
Franklin, AntonyUNSPECIFIED
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Blockchain; Deep Learning; Intrusion Detection System (IDS); Software-Defined Network (SDN); Unmanned Aerial Vehicles (UAVs)
Subjects: Computer science
Electrical Engineering
Divisions: Department of Computer Science & Engineering
Department of Electrical Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 01 Aug 2022 10:05
Last Modified: 01 Aug 2022 10:05
Publisher URL:
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