Network Traffic Fingerprinting for IIoT Device Identification: A Survey
Swinburne University of Technology · The University of Adelaide
Abstract
As the Industrial Internet of Things (IIoT) continues to expand, the need for effective device identification becomes critical for securing industrial environments. Network traffic fingerprinting has emerged as an important technique for IIoT device identification, leveraging the unique communication patterns embedded in network traffic. Despite significant efforts in this area, a comprehensive overview of the relevant research is still missing. To address the lack of comprehensive research, this paper, for the first time, identifies critical knowledge gaps constraining IIoT device identification through network traffic analysis: obscure fingerprint feature space, limited generalizability to unknowns, and…
Citation impact
- FWCI
- 104.88
- Percentile
- 100%
- References
- 111
Authors
7Topics & keywords
- Identification (biology)
- Computer science
- Computer security
- Computer network