PARALLEL DATA LAB

CASTELLAN:

Managing Distributed Intrusion Detection

Many organizations use intrusion detection systems (IDSs) to protect themselves against threats such as viruses and attacks. We are developing new self-securing devices (e.g., self-securing storage and NIC-based firewalls), to provide increased security by creating separate, smaller security domains. However, this distribution of security raises significant administrative challenges.

In this project, we are developing Castellan, a software tool for managing distributed intrusion detection systems. Castellan will support network administrators in:

  • Configuration - Setting appropriate policies on different self-securing devices.
  • Detection - Notification of security alerts.
  • Diagnosis - Investigating alerts to determine what action to take (if any).
  • Recovery - Using the logging and other enhanced features of self-securing devices to recover from intrusions.

We are currently in the design stages of Castellan and are talking with network administrators about their needs for managing distributed intrusion detection. A sketch of the Castellan interface follows.




People

FACULTY

Greg Ganger

STUDENTS

Ernest Chan

Acknowledgements

We thank the members and companies of the PDL Consortium: Amazon, Google, Hitachi Ltd., Honda, Intel Corporation, IBM, Jane Street, Meta, Microsoft Research, Oracle Corporation, Pure Storage, Salesforce, Samsung Semiconductor Inc., Two Sigma, and Western Digital for their interest, insights, feedback, and support.