Using internal sensors for computer intrusion detection
Abstract
This dissertation introduces the concept of using internal sensors to perform intrusion detection in computer systems. It shows its practical feasibility and discusses its characteristics and related design and implementation issues. We introduce a classification of data collection mechanisms for intrusion detection systems. At a conceptual level, these mechanisms are classified as direct and indirect monitoring. At a practical level, direct monitoring can be implemented using external or internal sensors. Internal sensors provide advantages with respect to reliability, completeness, timeliness and volume of data, in addition to efficiency and resistance against attacks. We introduce an architecture called ESP as a framework for building intrusion detection systems based on internal sensors. We describe in detail a prototype implementation based on the ESP architecture and introduce the concept of embedded detectors as a mechanism for localized data reduction. We show that it is possible to build both specific (specialized for a certain intrusion) and generic (able to detect different types of intrusions) detectors. Furthermore, we provide information about the types of data and places of implementation that are most effective in detecting different types of attacks. Finally, performance testing of the ESP implementation shows the impact that embedded detectors can have on a computer system. Detection testing shows that embedded detectors have the capability of detecting a significant percentage of new attacks.
Degree
Ph.D.
Advisors
Spafford, Purdue University.
Subject Area
Computer science
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