Runtime self-diagnosis and self-recovery infrastructure for embedded systems

Lei Sun, Yuki Kinebuchi, Tomohiro Katori, Tatsuo Nakajima

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

In this paper, a runtime self-diagnosis and self-recovery infrastructure is presented for embedded systems. Different from existing methods of off-line tracing system logs, our research focuses on analyzing system kernel data structures from runtime memory periodically against predefined constraints. If any violations have been detected, recovery functions are invoked. The prototype system is developed based on a system virtualization layer, above on which the guest operating system, diagnosis and recovery services run simultaneously. The infrastructure requires few modifications to the source code of operating system kernel, thus it can be easily adopted into existing embedded systems for quick implementation. It is also fully software-based without introducing any specific hardware; therefore it is costefficient. The experiments indicate that it can correctly detect and recover from several kernel security attacks with acceptable penalty to system performance.

本文言語English
ホスト出版物のタイトルSASO 2009 - 3rd IEEE International Conference on Self-Adaptive and Self-Organizing Systems
ページ284-285
ページ数2
DOI
出版ステータスPublished - 2009
イベントSASO 2009 - 3rd IEEE International Conference on Self-Adaptive and Self-Organizing Systems - San Francisco, CA, United States
継続期間: 2009 9 142009 9 18

出版物シリーズ

名前SASO 2009 - 3rd IEEE International Conference on Self-Adaptive and Self-Organizing Systems

Conference

ConferenceSASO 2009 - 3rd IEEE International Conference on Self-Adaptive and Self-Organizing Systems
CountryUnited States
CitySan Francisco, CA
Period09/9/1409/9/18

ASJC Scopus subject areas

  • Computer Science Applications
  • Hardware and Architecture
  • Software

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