Q: How privacy and data security were handled in previous collaborative or distributed detection systems?

• Centralized Detection System: Still Adopted but risks data aggregate and leakages
• Federated Learning (FL): Very promising but never adopted for a MANET IDS
• Differential Privacy: Conceptual yet lacks practical applicability
• Secure Aggregation Techniques: Very few in collaborative frameworks
• Trust Calculation Models: Common sharing of behavior data, at times compromising with privacy of user.

Future researchers seeking PhD research writing support and writing a structured literature review chapter for PhD should consider these points.

Gap Insight: This is another subject with much desired privacy versus security addressed issue and calls for features that will hence advance decentralized methods in privacy-preserving manner.