# A Systematic Review on Hybrid AI Models Integrating Machine Learning and Federated Learning
## 3 Background and Related Work
### Federated Learning: Principles and Challenges
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Ref.** & **Survey** & **Objective** \\ \hline \multirow{2}{*}{[37]} & \multirow{2}{*}{Federated learning for cybersecurity} & Comprehensive review of federated learning in edge and cloud computing for privacy-preserving threat detection. \\ \cline{2-3}  & & \\ \hline \multirow{2}{*}{[54]} & Federated learning-based model to lightweight IDSs for heterogeneous IoT networks & Comprehensive survey on FL specifically for IDSs in IoT environments. \\ \hline \multirow{2}{*}{[39]} & \multirow{2}{*}{Federated learning for cybersecurity concepts} & Explores real-time applications of federated learning in cybersecurity for attack detection and trust management. \\ \hline \multirow{2}{*}{[40]} & \multirow{2}{*}{Federated learning in adversarial environments: Testbed design and poisoning resilience in cybersecurity} & Introduces a testbed to evaluate FL-based IDSs under adversarial conditions, focusing on poisoning resilience and anomaly detection. \\ \hline \multirow{2}{*}{[41]} & Privacy-preserving federated learning for intrusion detection in IoT & Proposes a hybrid FL framework for intrusion detection in IoT networks that integrates homomorphic encryption and differential privacy. \\ \hline \multirow{2}{*}{[42]} & Federated learning for privacy-preserving intrusion detection in IoT & Implements a FedAvg-based FL model across multiple IoT nodes for intrusion detection. \\ \hline \multirow{2}{*}{[43]} & \multirow{2}{*}{Federated learning in IoT cybersecurity federated learning, such as latency and data privacy.} \\ \hline \multirow{2}{*}{[44]} & \multirow{2}{*}{FL techniques for cybersecurity federated learning in cybersecurity federated learning in cybersecurity federated learning in cybersecurity. \\ \hline \multirow{2}{*}{[45]} & \multirow{2}{*}{Federated learning support for cybersecurity leveraged to enhance cybersecurity.} \\ \hline \multirow{2}{*}{[46]} & \multirow{2}{*}{Detecting cyber threats in IoT with FL} & Demonstrates superior performance of FL over centralized learning in detecting IoT threats. \\ \hline \multirow{2}{*}{[58]} & \multirow{2}{*}{Deep learning and federated learning in cybersecurity enhanced cybersecurity and privacy.} \\ \cline{2-3}  & & \\ \hline \multirow{2}{*}{[47]} & FL-IDPP: A federated learning-based intrusion detection model for IoT & Introduces FL-IDPP, an RNN-based FL model that performs distributed intrusion detection in IoT networks. \\ \hline \multirow{2}{*}{[49]} & IoT intrusion detection & Reviews intrusion detection solutions for IoT with a focus on FL, explainable AI, and social psychology methods. \\ \hline \multirow{2}{*}{[51]} & Digital twin and federated learning enabled cyberthreat detection system for IoT networks & Combines digital twins and optimized FL to improve detection of zero-day threats in IoT with reduced latency and improved aggregation. \\ \hline \multirow{2}{*}{[50]} & \multirow{2}{*}{Federated learning for Internet of Things} & Presents the FedIoT platform and FedDetect algorithm, showing how FL improves attack detection and system efficiency on real IoT devices. \\ \hline \multirow{2}{*}{[59]} & Enhancing privacy-preserving intrusion detection with federated learning & Shows that FL-based models outperform centralized deep learning in detecting cyberattacks in privacy-sensitive environments. \\ \hline \multirow{2}{*}{[55]} & Privacy-preserving federated learning-based intrusion detection for IoT & Develops a lightweight FL framework using FedAvg that maintains high detection rates across heterogeneous IoT environments. \\ \hline \multirow{2}{*}{[52]} & \multirow{2}{*}{A scalable vertical federated learning framework for analytics in the cybersecurity domain} & Proposes and evaluates a vertical FL framework that is adaptable, privacy-compliant, and scalable for real-world cybersecurity analytics. \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Evaluating federated learning for cybersecurity solutions.