Antilizer: run time self-healing security for wireless sensor networks
- Submitting institution
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University of Greenwich
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 24402
- Type
- E - Conference contribution
- DOI
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10.1145/3286978.3287029
- Title of conference / published proceedings
- Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services - MobiQuitous '18
- First page
- 107
- Volume
- 0
- Issue
- -
- ISSN
- -
- Open access status
- -
- Month of publication
- -
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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3
- Research group(s)
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-
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is one of the first fully-distributed self-healing security solutions for wireless sensor networks. Each sensor uses only self-collected information to not only infer malicious activities but also provide an automated response to avoid their effects at run-time. Antilizer’s low operational overheads (less than 1%) enable its execution on low-cost resource-limited sensors, which opens opportunities for deploying these securely in critical infrastructures.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
