Context sensitive anomaly monitoring of process control flow to detect mimicry attacks and impossible paths

Haizhi Xu, Wenliang Du, Steve J. Chapin

Research output: Chapter in Book/Entry/PoemChapter

20 Scopus citations

Abstract

Many intrusions amplify rights or circumvent defenses by issuing system calls in ways that the original process did not. Defense against these attacks emphasizes preventing attacking code from being introduced to the system and detecting or preventing execution of the injected code. Another approach, where this paper fits in, is to assume that both injection and execution have occurred, and to detect and prevent the executing code from subverting the target system. We propose a method using waypoints: marks along the normal execution path that a process must follow to successfully access operating system services. Waypoints actively log trustworthy context information as the program executes, allowing our anomaly monitor to both monitor control flow and restrict system call permissions to conform to the legitimate needs of application functions. We describe our design and implementation of waypoints and present results showing that waypoint-based anomaly monitors can detect a subset of mimicry attacks and impossible paths.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsErland Jonsson, Magnus Almgren, Alfonso Valdes
PublisherSpringer Verlag
Pages21-38
Number of pages18
ISBN (Print)3540231234, 9783540231233
DOIs
StatePublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3224
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Anomaly detection
  • Context sensitive
  • Control flow monitoring
  • Impossible paths
  • Mimicry attacks
  • Waypoint

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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