Blended Ensemble Learning for Robust MITM Attack Detection and Classification in Smart Grid-Reference-Cited by-同舟云学术

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Blended Ensemble Learning for Robust MITM Attack Detection and Classification in Smart Grid

Published:2023-09-25 Issue: Volume: Page:1-6
ISSN:
Container-title:2023 33rd Australasian Universities Power Engineering Conference (AUPEC)
language:
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Author:

Shafin Sakib Shahriar¹,Ashiqur Rahman Quazi²,Gondal Iqbal³,Karmakar Gour⁴,Hossain Mondal M. Rubaiyat⁵

Affiliation:

1. Centre for Smart Analytics Federation University Australia,Ballarat,Australia

2. Bangladesh University of Engineering & Technology,Department of Electrical & Electronic Engg,Dhaka,Bangladesh

3. SCT, STEM College RMIT University,Melbourne,Australia

4. Institute of Innovation, Science and Sustainability Federation University Australia,Ballarat,Australia

5. Institute of Information & Communication Technology Bangladesh University of Engineering & Technology,Dhaka,Bangladesh

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10502395/10502438/10502977.pdf?arnumber=10502977

Reference19 articles.

1. Measuring Trustworthiness of Smart Meters Leveraging Household Energy Consumption Profile

2. Classifying resilience approaches for protecting smart grids against cyber threats

3. Ir-alert-h-16-05601,2016

4. Man‐in‐the‐middle attacks and defence in a power system cyber‐physical testbed

5. Obfuscated Memory Malware Detection in Resource-Constrained IoT Devices for Smart City Applications

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