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Updated: Sep 17, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

Enhanced security for IoT cloud environments using EfficientNet and enhanced football team training algorithm.

Jian Cui¹, Lan Shi², Ahmed Alkhayyat³

¹College of Physical Education Science, Anshan Normal University, Liaoning, Anshan, 114000, China. cuijan021004@163.com.

Scientific Reports

|July 2, 2025

Summary

This summary is machine-generated.

This study introduces an EfficientNet/EFTTA model for advanced intrusion detection in Internet of Things (IoT) cloud environments. The novel approach significantly enhances security by accurately identifying cyber threats with over 98.56% accuracy.

Keywords:

Cloud computing Cybersecurity EfficientNet Enhanced football team training algorithm Intrusion detection IoT Machine learning Metaheuristic algorithm Optimization techniques

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Published on: September 8, 2023

Area of Science:

Cybersecurity
Artificial Intelligence
Cloud Computing

Background:

The proliferation of Internet of Things (IoT) devices expands the attack surface in IoT-cloud environments.
Securing these increasingly complex systems against diverse cyber threats is a significant challenge.

Purpose of the Study:

To develop an innovative intrusion detection system for IoT-cloud environments.
To enhance the accuracy and efficiency of anomaly and intrusion detection in IoT networks.

Main Methods:

Integration of EfficientNet, a deep learning model, with the Enhanced Football Team Training Algorithm (EFTTA), a metaheuristic optimization technique.
Performance evaluation using standard datasets (NSL-KDD and BoT-IoT) and comparison with existing intrusion detection methods.

Main Results:

The proposed EfficientNet/EFTTA model demonstrated superior performance compared to existing techniques.
Achieved high accuracy rates: over 98.56% on NSL-KDD and 99.1% on BoT-IoT datasets.
Indicated enhanced capability in identifying anomalies and intrusions within IoT-cloud infrastructures.

Conclusions:

The EfficientNet/EFTTA model offers a promising and effective solution for securing IoT-cloud infrastructures.
The integration of deep learning and metaheuristics provides a robust framework for advanced intrusion detection.
The findings highlight the potential of the proposed method to significantly improve the protection of connected systems.