A Secure Privacy-Preserving Data Aggregation Model in Wearable Wireless Sensor Networks. (7th October 2015)
- Record Type:
- Journal Article
- Title:
- A Secure Privacy-Preserving Data Aggregation Model in Wearable Wireless Sensor Networks. (7th October 2015)
- Main Title:
- A Secure Privacy-Preserving Data Aggregation Model in Wearable Wireless Sensor Networks
- Authors:
- Zhang, Changlun
Li, Chao
Zhang, Jian - Other Names:
- Zhu Jiang Academic Editor.
- Abstract:
- Abstract : With the rapid development and widespread use of wearable wireless sensors, data aggregation technique becomes one of the most important research areas. However, the sensitive data collected by sensor nodes may be leaked at the intermediate aggregator nodes. So, privacy preservation is becoming an increasingly important issue in security data aggregation. In this paper, we propose a security privacy-preserving data aggregation model, which adopts a mixed data aggregation structure. Data integrity is verified both at cluster head and at base station. Some nodes adopt slicing technology to avoid the leak of data at the cluster head in inner-cluster. Furthermore, a mechanism is given to locate the compromised nodes. The analysis shows that the model is robust to many attacks and has a lower communication overhead.
- Is Part Of:
- Journal of electrical and computer engineering. Volume 2015(2015)
- Journal:
- Journal of electrical and computer engineering
- Issue:
- Volume 2015(2015)
- Issue Display:
- Volume 2015, Issue 2015 (2015)
- Year:
- 2015
- Volume:
- 2015
- Issue:
- 2015
- Issue Sort Value:
- 2015-2015-2015-0000
- Page Start:
- Page End:
- Publication Date:
- 2015-10-07
- Subjects:
- Computer engineering -- Periodicals
Electrical engineering -- Periodicals
621.3905 - Journal URLs:
- https://www.hindawi.com/journals/jece/ ↗
- DOI:
- 10.1155/2015/104286 ↗
- Languages:
- English
- ISSNs:
- 2090-0147
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 10787.xml