Fed-Avis: A Lightweight Federated Learning Assisted Anti-Vehicle Infiltration System

Author:

Agrawal Dewesh1ORCID,Singh Gurpreet1ORCID,Singh Harinderjit1ORCID,Singh Kulvir1ORCID,Jha Prianshu1ORCID,Patel Yashwant Singh1ORCID

Affiliation:

1. Computer Science & Engineering, Thapar Institute of Engineering & Technology, India

Publisher

ACM

Reference14 articles.

1. Shaashwat Agrawal, Sagnik Sarkar, Ons Aouedi, Gokul Yenduri, Kandaraj Piamrat, Mamoun Alazab, Sweta Bhattacharya, Praveen Kumar Reddy Maddikunta, and Thippa Reddy Gadekallu. 2022. Federated learning for intrusion detection system: Concepts, challenges and future directions. Computer Communications (2022).

2. Sourasekhar Banerjee, Yashwant Singh Patel, Pushkar Kumar, and Monowar Bhuyan. 2023. Towards Post-Disaster Damage Assessment Using Deep Transfer Learning and GAN-Based Data Augmentation(ICDCN ’23). Association for Computing Machinery, New York, NY, USA, 372–377.

3. Daniel J Beutel, Taner Topal, Akhil Mathur, Xinchi Qiu, Javier Fernandez-Marques, Yan Gao, Lorenzo Sani, Kwing Hei Li, Titouan Parcollet, Pedro Porto Buarque de Gusmão, 2020. Flower: A friendly federated learning research framework. arXiv preprint arXiv:2007.14390 (2020).

4. Big Data

5. Bhavya; Singal Gaurav; Rao D Vijay Gupta Priyanka; Pareek. 2021. Military and Civilian Vehicles Classification Mendeley Data V1. https://data.mendeley.com/datasets/njdjkbxdpn/1

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