Summary of Swarm Intelligence-driven Client Selection For Federated Learning in Cybersecurity Applications, by Koffka Khan and Wayne Goodridge
Swarm Intelligence-Driven Client Selection for Federated Learning in Cybersecurity applications
by Koffka Khan, Wayne Goodridge
First submitted to arxiv on: 28 Nov 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper addresses a gap in Federated Learning (FL) research by evaluating Swarm Intelligence Optimization (SI) algorithms for client selection in decentralized FL with a focus on cybersecurity applications. The study evaluates nine SI algorithms across four experimental scenarios to identify their adaptability and robustness. Results show that Grey Wolf Optimization (GWO) achieves the highest accuracy, recall, and F1-score across all configurations, while Particle Swarm Optimization (PSO) and Cuckoo Search also demonstrate strong performance. These findings highlight the potential of SI algorithms in addressing decentralized and adversarial FL challenges, offering scalable and resilient solutions for cybersecurity applications such as intrusion detection in IoT and large-scale networks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at a special kind of machine learning called Federated Learning (FL). It’s used to help computers work together without sharing their data. The problem is that when computers have different kinds of data, it can be hard to make sure they all agree on what’s important. This paper tries to solve this problem by using special algorithms called Swarm Intelligence Optimization (SI) algorithms. They tested nine different SI algorithms in four different situations to see which ones worked best. The results show that one algorithm, called Grey Wolf Optimization (GWO), did the best job of finding patterns and making predictions. This could be useful for things like detecting intruders on computers or networks. |
Keywords
» Artificial intelligence » F1 score » Federated learning » Machine learning » Optimization » Recall
