The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
An Efficient Distributed Trust Model for Wireless Sensor Networks
Abstract
Trust models have been recently suggested as an effective security mechanism for Wireless Sensor Networks (WSNs). Considerable research has been done on modeling trust. However, most current research work only takes communication behavior into account to calculate sensor nodes' trust value, which is not enough for trust evaluation due to the widespread malicious attacks. In this paper, we propose an Efficient Distributed Trust Model (EDTM) for WSNs. First, according to the number of packets received by sensor nodes, direct trust and recommendation trust are selectively calculated. Then, communication trust, energy trust and data trust are considered during the calculation of direct trust. Furthermore, trust reliability and familiarity are defined to improve the accuracy of recommendation trust. The proposed EDTM can evaluate trustworthiness of sensor nodes more precisely and prevent the security breaches more effectively. Simulation results show that EDTM outperforms other similar models, e.g., NBBTE trust model.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Opportunities and Challenges of Wireless Sensor Networks in Smart Grid
Gungor, V. C., Lu, B., & Hancke, G. P. (2010) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2009.2039455 · Cited by 1,368
Distributed optimization in sensor networks
Rabbat, M., & Nowak, R. (2004) · Proceedings of the 3rd international symposium on Information processing in sensor networks · doi:10.1145/984622.984626 · Cited by 901
Reputation-based framework for high integrity sensor networks
Ganeriwal, S., Balzano, L. K., & Srivastava, M. B. (2008) · ACM Transactions on Sensor Networks · doi:10.1145/1362542.1362546 · Cited by 808
Reputation-based framework for high integrity sensor networks
Ganeriwal, S., & Srivastava, M. B. (2004) · Proceedings of the 2nd ACM workshop on Security of ad hoc and sensor networks · doi:10.1145/1029102.1029115 · Cited by 583
Security and privacy in sensor networks
Chan, H., & Perrig, A. (2003) · Computer · doi:10.1109/mc.2003.1236475 · Cited by 519
Trust Computations and Trust Dynamics in Mobile Adhoc Networks: A Survey
Govindan, K., & Mohapatra, P. (2012) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2011.042711.00083 · Cited by 367
An Algebra for Assessing Trust in Certification Chains.
Jøsang, A. (1999) · Cited by 333
Management and applications of trust in Wireless Sensor Networks: A survey
Han, G., Jiang, J., Shu, L., Niu, J., & Chao, H.-C. (2014) · Journal of Computer and System Sciences · doi:10.1016/j.jcss.2013.06.014 · Cited by 247
Self-citationHuang, Y., Hsieh, M., Chao, H., Hung, S., & Park, J. (2009) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2009.090505 · Cited by 229
Feng, R., Xu, X., Zhou, X., & Wan, J. (2011) · Sensors · doi:10.3390/s110201345 · Cited by 184
Cited by
A synergetic trust model based on SVM in underwater acoustic sensor networks
Han, G., He, Y., Jiang, J., Wang, N., Guizani, M., & Ansere, J. A. (2019) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2019.2939179 · Cited by 106
Self-citationKey Challenges and Emerging Technologies in Industrial IoT Architectures: A Review
Mirani, A. A., Velasco-Hernandez, G., Awasthi, A., & Walsh, J. (2022) · Sensors · doi:10.3390/s22155836 · Cited by 119
Metadata
- Authors
- Jiang, J., Han, G., Wang, F., Shu, L., & Guizani, M.
- Venue
- IEEE Transactions on Parallel and Distributed Systems
- Published
- 2015-05-01
- Volume
- 26
- Issue
- 5
- Pages
- 1228-1237
- ISSN
- 1045-9219 (ISSN-L)
- OpenAlex
- W2171775586
- Cited by
- 287
- References
- 13
- FWCI
- 23.11
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: An Efficient Distributed Trust Model for Wireless Sensor Networks. https://app.cochat.ai/papers/10.1109/tpds.2014.2320505
- The paper
- Jiang, J., Han, G., Wang, F., Shu, L., & Guizani, M. (2015). An Efficient Distributed Trust Model for Wireless Sensor Networks. IEEE Transactions on Parallel and Distributed Systems. https://doi.org/10.1109/tpds.2014.2320505
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.