Open Accessk-anonymity based framework for privacy preserving data collection in wireless sensor networks
Author(s) -
HAYRETDİN BAHŞİ,
Albert Levі
Publication year - 2010
Publication title -
turkish journal of electrical engineering and computer sciences/elektrik
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.225
H-Index - 30
eISSN - 1303-6203
pISSN - 1300-0632
DOI - 10.3906/elk-0907-120
Subject(s) - encryption , computer science , k anonymity , wireless sensor network , anonymity , computer network , information loss , information privacy , generalization , cluster analysis , computer security , mathematics , mathematical analysis , artificial intelligence , machine learning
In this paper; k-anonymity notion is adopted to be used in wireless sensor networks (WSN) as a security framework with two levels of privacy. A base level of privacy is provided for the data shared with semi-trusted sink and a deeper level of privacy is provided against eavesdroppers. In the proposed method, some portions of data are encrypted and the rest is generalized. Generalization shortens the size of the data transmitted in the network causing energy saving at the cost of information loss. On the other hand, encryption provides anonymization with no information loss and without saving energy. Thus, there is a tradeoff between information loss and energy saving. In our system, this tradeoff is intelligently managed by a system parameter, which adjusts the amount of data portions to be encrypted. We use a method based on bottom up clustering that chooses the data portions to be encrypted among the ones that cause maximum information loss when generalized. In this way; a high degree of energy saving is realized within the given limits of information loss. Our analysis shows that the proposed method achieves the desired privacy levels with low information loss and with considerable energy saving