Smart Flood Detection with AI and Blockchain Integration in Saudi Arabia Using Drones

被引:8
作者
Alsumayt, Albandari [1 ]
El-Haggar, Nahla [1 ]
Amouri, Lobna [1 ]
Alfawaer, Zeyad M. M. [1 ]
Aljameel, Sumayh S. S. [2 ]
机构
[1] Imam Abdulrahman Bin Faisal Univ, Appl Coll, Comp Sci Dept, POB 1982, Dammam 31441, Saudi Arabia
[2] Imam Abdulrahman Bin Faisal Univ, Coll Comp Sci & Informat Technol, Saudi Aramco Cybersecur Chair, Dept Comp Sci, POB 1982, Dammam 31441, Saudi Arabia
关键词
UAVs; IPFS; FDSS; DeepAL; PHE; SGD; IoT; IoD; MEC; blockchain; homomorphic; AI; AUTHENTICATION PROTOCOL; UAV; SCHEME; INTERNET; IDENTITY; CLASSIFICATION; COMMUNICATION; CHALLENGES; MECHANISM;
D O I
10.3390/s23115148
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Global warming and climate change are responsible for many disasters. Floods pose a serious risk and require immediate management and strategies for optimal response times. Technology can respond in place of humans in emergencies by providing information. As one of these emerging artificial intelligence (AI) technologies, drones are controlled in their amended systems by unmanned aerial vehicles (UAVs). In this study, we propose a secure method of flood detection in Saudi Arabia using a Flood Detection Secure System (FDSS) based on deep active learning (DeepAL) based classification model in federated learning to minimize communication costs and maximize global learning accuracy. We use blockchain-based federated learning and partially homomorphic encryption (PHE) for privacy protection and stochastic gradient descent (SGD) to share optimal solutions. InterPlanetary File System (IPFS) addresses issues with limited block storage and issues posed by high gradients of information transmitted in blockchains. In addition to enhancing security, FDSS can prevent malicious users from compromising or altering data. Utilizing images and IoT data, FDSS can train local models that detect and monitor floods. A homomorphic encryption technique is used to encrypt each locally trained model and gradient to achieve ciphertext-level model aggregation and model filtering, which ensures that the local models can be verified while maintaining privacy. The proposed FDSS enabled us to estimate the flooded areas and track the rapid changes in dam water levels to gauge the flood threat. The proposed methodology is straightforward, easily adaptable, and offers recommendations for Saudi Arabian decision-makers and local administrators to address the growing danger of flooding. This study concludes with a discussion of the proposed method and its challenges in managing floods in remote regions using artificial intelligence and blockchain technology.
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页数:30
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共 77 条
[11]   A Survey of Blockchain-Based Strategies for Healthcare [J].
De Aguiar, Erikson Julio ;
Faical, Bruno S. ;
Krishnamachari, Bhaskar ;
Ueyama, Jo .
ACM COMPUTING SURVEYS, 2020, 53 (02)
[12]   A smart lightweight privacy preservation scheme for IoT-based UAV communication systems [J].
Deebak, B. D. ;
Al-Turjman, Fadi .
COMPUTER COMMUNICATIONS, 2020, 162 :102-117
[13]   UAVouch: A Secure Identity and Location Validation Scheme for UAV-Networks [J].
Emygdio de Melo, Carlos Felipe ;
Silva, Tulio Dapper E. ;
Boeira, Felipe ;
Stocchero, Jorgito Matiuzzi ;
Vinel, Alexey ;
Asplund, Mikael ;
de Freitas, Edison Pignaton .
IEEE ACCESS, 2021, 9 :82930-82946
[14]   A secure authentication scheme framework for mobile-sinks used in the Internet of Drones applications [J].
Ever, Yoney Kirsal .
COMPUTER COMMUNICATIONS, 2020, 155 :143-149
[15]   Privacy Preserving Machine Learning with Homomorphic Encryption and Federated Learning [J].
Fang, Haokun ;
Qian, Quan .
FUTURE INTERNET, 2021, 13 (04)
[16]   A Survey of Homomorphic Encryption for Nonspecialists [J].
Fontaine, Caroline ;
Galand, Fabien .
EURASIP JOURNAL ON INFORMATION SECURITY, 2007, (01)
[17]   Blockchain-Enabled Trustworthy Group Communications in UAV Networks [J].
Gai, Keke ;
Wu, Yulu ;
Zhu, Liehuang ;
Choo, Kim-Kwang Raymond ;
Xiao, Bin .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 22 (07) :4118-4130
[18]   FLoBC: A Decentralized Blockchain-Based Federated Learning Framework [J].
Ghanem, Mohamed ;
Dawoud, Fadi ;
Gamal, Habiba ;
Soliman, Eslam ;
El-Batt, Tamer ;
El-Batt, Tamer .
2022 FOURTH INTERNATIONAL CONFERENCE ON BLOCKCHAIN COMPUTING AND APPLICATIONS (BCCA), 2022, :85-92
[19]   A convolutional neural network for detecting sea turtles in drone imagery [J].
Gray, Patrick C. ;
Fleishman, Abram B. ;
Klein, David J. ;
McKown, Matthew W. ;
Bezy, Vanessa S. ;
Lohmann, Kenneth J. ;
Johnston, David W. .
METHODS IN ECOLOGY AND EVOLUTION, 2019, 10 (03) :345-355
[20]   Research on medical data security sharing scheme based on homomorphic encryption [J].
Guo, Lihong ;
Gao, Weilei ;
Cao, Ye ;
Lai, Xu .
MATHEMATICAL BIOSCIENCES AND ENGINEERING, 2023, 20 (02) :2261-2279