---
res:
  bibo_abstract:
  - Autonomous adaptation in self-adapting embedded real-time systems introduces novel
    risks as it may lead to unforeseen system behavior. An anomaly detection framework
    integrated in a real-time operating system can ease the identification of such
    suspicious novel behavior and, thereby, offers the potential to enhance the reliability
    of the considered self-x system. However, anomaly detection is based on knowledge
    about normal behavior. When dealing with self-reconfiguring applications, normal
    behavior changes. Hence, knowledge base requires adaptation or even re-construction
    at runtime. The stringent restrictions of real-time systems considering runtime
    and memory consumption make this task to a really challenging problem. We present
    our idea for online construction of application behavior knowledge that does not
    rely on training phase. The applications' behavior is defined by the application's
    system call invocations. For the knowledge base, we exploit suffix trees as they
    offer potentials to represent application behavior patterns and associated information
    in a compact manner. The online algorithm provided by suffix trees is a basis
    to construct the knowledge base with low computational effort. Anomaly detection
    and classification is integrated into the online construction method. New behavioral
    patterns do not unconditionally update the behavior knowledge base. They are evaluated
    in a context-related manner inspired by Danger Theory, a special discipline of
    artificial immune systems. Copyright © 2015 John Wiley & Sons, Ltd.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Franz-Josef
      foaf_name: Rammig, Franz-Josef
      foaf_surname: Rammig
  - foaf_Person:
      foaf_givenName: Katharina
      foaf_name: Stahl, Katharina
      foaf_surname: Stahl
  dct_date: 2015^xs_gYear
  dct_language: eng
  dct_title: Online behavior classification for anomaly detection in self-x real-time
    systems@
...