But, with global initiatives like the EU AI Act and U.S. AI Strategy highlight the importance of ethical AI regulation, especially in cybersecurity.
A report shared with Cyber Security News by a group of cybersecurity analysts consisting of Jose L. Hernandez-Ramos, Georgios Karopoulos, Efstratios Chatzoglou, Vasileios Kouliaridis, Enrique Marmol, Aurora Gonzalez-Vidal, and Georgios Kambourakis, revealed the latest development in the cybersecurity field, which is the decentralized learning approach known as “Federated Learning (FL).”
Under this decentralized approach, the ML models are built without sharing the end nodes’ data by utilizing a certain aggregation.
Federated Learning-Based IDS
For the development of systems and applications based on Machine Learning, this decentralized approach is very important, and not only that, but even this new approach also helps secure the privacy of end users.
So, it seems that the complete mechanism of this new approach, Federated Learning (FL), is comprehensive and advanced in nature, as the security systems can use this approach for better protection and defense mechanisms.
The IDS (Intrusion Detection System) detects the threats in IT/OT systems, and the FL-based IDS growth links to accurate evaluation datasets.
Besides this, the initial evolution of IDSs was mainly focused on the approaches that are signature-based, but the recent combination of IDS with an FL-based approach seems promising and far more efficient than the previous approaches.
In this scenario, the neural networks (NNs) used in IDS match the two key elements, and here below, we have mentioned them:-
Input features
Classes
Moreover, the RL (Reinforcement Learning), an ML branch, has agents learn to maximize rewards through trial and error. While it categorizes into the following methods:-
Value-based
Policy-based
Model-based
Challenges Faced
Here below, we have mentioned all the challenges and future trends for FL-enabled IDS approaches:-
Security
Privacy
Aggregator as bottleneck
Data heterogeneity
Device heterogeneity
Computation requirements
Communication requirements
The growth of FL in IDS is clearly notable and skyrocketed rapidly due to its following key features:-
Decentralized
Collaborative
Privacy-protection
Overall, it’s been concluded that this new decentralized approach could be game-changing in the field of cybersecurity.