Federated Learning for intrusion detection system: Concepts, challenges and future directions
Vellore Institute of Technology University · Laboratoire des Sciences du Numérique de Nantes · +3 more institutions
Indexed inarxivcrossref
Abstract
No abstract available for this paper.
Citation impact
397
total citations
- FWCI
- 49.39
- Percentile
- 100%
- References
- 155
Citations per year
Authors
9- SAShaashwat AgrawalCorresponding
Vellore Institute of Technology University
- SSSagnik Sarkar
Vellore Institute of Technology University
- OAOns Aouedi
Laboratoire des Sciences du Numérique de Nantes, IMT Atlantique, Nantes Université
- GYGokul Yenduri
Vellore Institute of Technology University
- KPKandaraj Piamrat
Laboratoire des Sciences du Numérique de Nantes, IMT Atlantique, Nantes Université
Topics & keywords
Topics
Keywords
- Computer science
- Intrusion detection system
- Anomaly detection
- Implementation
- Scope (computer science)
- Computer security
- Distributed computing
- Artificial intelligence
UN Sustainable Development Goals
- Industry, innovation and infrastructure
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