Intrusion Detection in Distributed Systems: An Abstraction-Based Approach(9 Advances in Information Security)

Intrusion detection systems (IDS) are usually deployed along with other preventive security mechanisms, such as access control and authentication, as a second line of defense that protects information systems. Intrusion detection complements the protective mechanisms to improve the system security. Moreover, even if the preventive security mechanisms can protect information systems successfully, it is still desirable to know what intrusions have happened or are happening, so that the users can understand the security threats and risks and thus be better prepared for future attacks. Intrusion detection techniques are traditionally categorized into two classes: anomaly detection and misuse detection. Anomaly detection is based on the normal behavior of a subject (a user or a system); any action that significantly deviates from the normal behaviour is considered intrusive. Misuse detection catches intrusions in terms of characteristics of known attacks or system vulnerabilities; any action that conforms to the pattern of known attack or vulnerability is considered intrusive. Alternatively, IDS may be classified into host-based IDSs, distributed IDSs, and network based IDSs according to the source of the audit information used by each IDS. Host-based IDSs get audit data from host audit trails and usually aim at detecting attacks against a single host; distributed IDSs gather audit data from multiple hosts and possibly the network and connects the hosts, aiming at detecting attacks involving multiple hosts; network-based IDSs use network traffic as the audit data source, relieving the burden on the hosts that usually provide normal computing services. Intrusion Detection In Distributed Systems: An Abstraction-Based Approach presents research contributions in three areas with respect to intrusion detection in distributed systems. The first contribution is an abstraction-based approach to addressing heterogeneity and autonomy of distributed environments. The second contribution is a formal framework for modelling requests among co-operative IDSs and its application to Common Intrusion Detection Framework (CIDF). The third contribution is a novel approach to coordinating different IDSs for distributed event correlation.

Table of Contents:
Dedication.- List of Figures.- List of Tables.- Preface.- Acknowledgments.- 1. INTRODUCTION.- 1 Computer Security and Intrusion Detection.- 2 Intrusion Detection in Distributed Systems.- 3 Summary of Contributions.- 4 Organization.- 2. AN OVERVIEW OF RELATED RESEARCH.- 3. SYSTEM VIEW AND EVENT HISTORY.- 1 System View and Event History.- 4. MODELING REQUEST AMONG COOPERATING INTRUSION DETECTION SYSTEMS.- 1 Query.- 2 Scaling to Large and Heterogeneous Environments.- 3 Discussion.- 5. EXTENDING COMMON INTRUSION DETECTION FRAMEWORK (CIDF) TO SUPPORT QUERIES.- 1 Background.- 2 A Query Facility for CIDF.- 3 Impact on CIDF.- 6. A HIERARCHICAL MODEL FOR DISTRIBUTED ATTACKS.- 1 Misuse Signature.- 2 Defining System Views Using Signatures: A Hierarchical Model.- 3 Discussion.- 7. DECENTRALIZED DETECTION OF DISTRIBUTED ATTACKS.- 1 Serializable Signatures.- 2 Detection Task and Workflow Tree.- 3 Execution of Detection Tasks.- 4 Optimization.- 5 Generating Workflow Tree.- 8. CARDS: AN EXPERIMENTAL SYSTEM FOR DETECTING DISTRIBUTED ATTACKS.- 1 CARDS Architecture.- 2 System Design Issues.- 3 Prototype Implementation.- 9. CONCLUSION.- Appendices.- References.

About the Author :
Dr. Sushil Jajodia is Professor and Chairman of the Dept. of Information and Software Engineering, and Director of the Center for Secure Information Systems at the George Mason University, Fairfax, Virginia, USA