教師資料查詢 | 類別: 期刊論文 | 教師: 李思壯LI SZU CHUANG (瀏覽個人網頁)

標題:DE-IDENTIFICATION TECHNIQUE FOR IOT WIRELESS SENSOR NETWORK PRIVACY PROTECTION
學年105
學期1
出版(發表)日期2017/01/15
作品名稱DE-IDENTIFICATION TECHNIQUE FOR IOT WIRELESS SENSOR NETWORK PRIVACY PROTECTION
作品名稱(其他語言)
著者Yennun Huang; Szu-Chuang Li; Bo-Chen Tai; Chieh-Ming Chang; Dmitrii I. Kaplun; Denis N. Butusov
單位
出版者
著錄名稱、卷期、頁數Journal of Computer Science and Information 10(1)
摘要As the IoT ecosystem becoming more and more mature, hardware and software vendors are trying create new value by connecting all kinds of devices together via IoT. IoT devices are usually equipped with sensors to collect data, and the data collected are transmitted over the air via different kinds of wireless connection. To extract the value of the data collected, the data owner may choose to seek for third-party help on data analysis, or even of the data to the public for more insight. In this scenario it is important to protect the released data from privacy leakage. Here we propose that differential privacy, as a de-identification technique, can be a useful approach to add privacy protection to the data released, as well as to prevent the collected from intercepted and decoded during over-the-air transmission. A way to increase the accuracy of the count queries performed on the edge cases in a synthetic database is also presented in this research.
關鍵字differential privacy;Internet of Things;sensor network
語言英文
ISSN2502-9274
期刊性質國外
收錄於
產學合作
通訊作者Szu Chuang Li
審稿制度
國別印度尼西亞共和國
公開徵稿
出版型式,電子版
相關連結
SDGs
  • 和平正義與有力的制度,產業創新與基礎設施
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