• 综合
  • 标题
  • 关键词
  • 摘要
  • 学者
  • 期刊-刊名
  • 期刊-ISSN
  • 会议名称
搜索

作者:

Zhang, Yingjia (Zhang, Yingjia.) | Wan, Yunfeng (Wan, Yunfeng.)

收录:

EI Scopus

摘要:

In some IoT applications, the sensing layer often collects images and various temporal data. Usually, some temporal data represents sensitive or private information. In order to protect the temporal data, and at the same to reduce data traffic transmitted through the Internet of Things, this paper proposes a secure transmission method for sensitive data based on Arnold transform and steganography technique. In this method, an Arnold transform which is usually used in scrambling images is applied to encrypt sensitive sequential data. It is achieved by re-organizing the position of data elements in a matrix, not necessarily a square matrix. Then, the sensitive data in the matrix is embedded row by row in a carrier image using a novel data hiding technique, namely, capacity adaptive algorithm. Through the above dual processing, the sensitive data is less likely to be detected by a third party during transmission. The experimental results indicate that the method achieves high performance in safeguarding the security and privacy of sensitive data. In addition, the method offers numerous benefits, including high efficiency and scalability in data hiding capacity, and low computational cost, making it widely applicable for practical data transmission. © 2024 SPIE.

关键词:

Matrix algebra Adaptive algorithms Image processing Sensitive data Steganography Internet of things

作者机构:

  • [ 1 ] [Zhang, Yingjia]Faculty of Information Technology, Beijing University of Technology, Beijing; 10021, China
  • [ 2 ] [Wan, Yunfeng]Faculty of Information Technology, Beijing University of Technology, Beijing; 10021, China

通讯作者信息:

电子邮件地址:

查看成果更多字段

相关关键词:

相关文章:

来源 :

ISSN: 0277-786X

年份: 2024

卷: 13063

语种: 英文

被引次数:

WoS核心集被引频次:

SCOPUS被引频次:

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

近30日浏览量: 0

归属院系:

在线人数/总访问数:514/4978698
地址:北京工业大学图书馆(北京市朝阳区平乐园100号 邮编:100124) 联系我们:010-67392185
版权所有:北京工业大学图书馆 站点建设与维护:北京爱琴海乐之技术有限公司