1 / 40

Intrusion Detection Systems

Intrusion Detection Systems. Francis Chang <francis@cse.ogi.edu> Systems Software Lab OGI. [1] M. Crosbie, B. Kuperman, " A Building Block Approach to Intrusion Detection " [2] M. Wetz, Andrew Hutchison, " Interfacing Trusted Applications with Intrusion Detection Systems "

tana
Download Presentation

Intrusion Detection Systems

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Intrusion Detection Systems Francis Chang <francis@cse.ogi.edu> Systems Software Lab OGI

  2. [1] M. Crosbie, B. Kuperman, "A Building Block Approach to Intrusion Detection" [2] M. Wetz, Andrew Hutchison, "Interfacing Trusted Applications with Intrusion Detection Systems" [3] Y. Zhang, W. Lee, "Intrusion Detection in Wireless Ad-Hoc Networks" [4] G. Mansfield, K. Ohta, Y. Takei, N. Kato, Y. Nemoto, "Towards Trapping Wily Intruders in the Large" The Papers

  3. A building Block Approachto Intrusion Detection Let’s first look at the first paper… [1] M. Crosbie, B. Kuperman, "A Building Block Approach to Intrusion Detection"

  4. A building Block Approachto Intrusion Detection A new spin on how to build an IDS – “..motors the system looking for misuse actions that are indicative of attack. These misuses actions are called building blocks.” Need for a better data source for IDS (IDDS – Intrusion Detection Data Source)

  5. A building Block Approachto Intrusion Detection Examples of building blocks: • Modification of a system file • Unexpected change user privileges of a running process • Modify log files • Change a global symbolic link • Creating setuid programs

  6. A building Block Approachto Intrusion Detection So what did they do? Build an in-kernel IDDS.

  7. A building Block Approachto Intrusion Detection Crosbie/Kuperman argue that traditional IDS data sources are insufficient – let’s take a look at their argument.

  8. A building Block Approachto Intrusion Detection syslogd: • Often a popular IDS data source • Often syslogd is used when a daemon “starts up, change configuration, encounter an error, or some other unusual behaviour occurs”

  9. A building Block Approachto Intrusion Detection syslogd: (continued) • Crosbie/Kuperman argues that the quality of the log messages is completely dependent on the programmers who wrote the system daemons. • Early versions of syslogd could be attacked – buffer overflows, abnormal exits

  10. A building Block Approachto Intrusion Detection Network Packet Traces: • If only using network packet traces, you often lose context, and thus, cannot detect certain types of attacks.

  11. A building Block Approachto Intrusion Detection Why is an in-kernel approach good? • Time inside the kernel is “frozen” • In-kernel design is more resilient to attack

  12. Interfacing Trusted Apps The next paper - [2] M. Wetz, Andrew Hutchison, "Interfacing Trusted Applications with Intrusion Detection Systems"

  13. Interfacing Trusted Apps This is funny:

  14. Interfacing Trusted Apps The basic suggestion: Rewrite existing applications to take advantage of a syslogd/IDS system.

  15. Interfacing Trusted Apps

  16. Intrusion Detection in Wireless Ad-hoc Networks The problem: • Open Medium – attacks can come from anywhere, an go anywhere • No clear topology – network is continually changing – no central points

  17. Intrusion Detection in Wireless Ad-hoc Networks The solution: An IDS at every node Let’s take a closer look at the IDS…

  18. Intrusion Detection in Wireless Ad-hoc Networks

  19. Intrusion Detection in Wireless Ad-hoc Networks Detecting Abnormal Routing Updates – Give each IDS a built-in GPS, and watch for unexpected # of route changes. (Statistical analysis)

  20. Intrusion Detection in Wireless Ad-hoc Networks Detecting abnormal activities in other layers: Various independent monitors to detect anomolies in other protocol layers, and combine results into a confidence rating.

  21. Intrusion Detection in Wireless Ad-hoc Networks Respond to intrusion detection by reconstructing the routing tables, and routing around the compromised node.

  22. Towards Trapping Wily Intruders in the Large G. Mansfield, K. Ohta, Y. Takei, N. Kato, Y. Nemoto, "Towards Trapping Wily Intruders in the Large" The Basics: Monitor the network, and collect statistics. When the statistics deviate from “normal” behaviour, flag it. Extend SNMP to allow various networks to collaborate to track down the intruder

  23. Towards Trapping Wily Intruders in the Large When a network is under attack, there is often a lot of suspicious network traffic – There are usually more: • TCP-RESET packets • ICMP echo & response • ICMP Destination unreachable messages

  24. Towards Trapping Wily Intruders in the Large ICMP Echo: Often occur in high volume when a network is under attack: • Mapping out a network • DDOS attacks • SMURF Attacks – let’s take a look

  25. Towards Trapping Wily Intruders in the Large SMURF Attack 1.1.1.2 1.1.1.3 1.1.1.1 Ping 1.1.1.255 from 3.3.3.3 2.2.2.2 3.3.3.3

  26. Towards Trapping Wily Intruders in the Large SMURF Attack 1.1.1.2 1.1.1.3 Ping 1.1.1.255 from 3.3.3.3 1.1.1.1 2.2.2.2 3.3.3.3

  27. Towards Trapping Wily Intruders in the Large SMURF Attack 1.1.1.2 1.1.1.3 Echo Reply Echo Reply 1.1.1.1 2.2.2.2 3.3.3.3

  28. Towards Trapping Wily Intruders in the Large SMURF Attack 1.1.1.2 1.1.1.3 1.1.1.1 Many Echo Responses 2.2.2.2 3.3.3.3

  29. Towards Trapping Wily Intruders in the Large TCP Resets: They do not occur too frequently in normal network traffic – but very often when a network is being attacked. Eg. • Port Scanning • Inverse Mapping – let’s take a look at this.

  30. Towards Trapping Wily Intruders in the Large Inverse Mapping (Successful routing) 1.1.1.2 1.1.1.3 1.1.1.1 ACK from 1.1.1.2 2.2.2.2 2.2.2.3

  31. Towards Trapping Wily Intruders in the Large Inverse Mapping (Successful routing) 1.1.1.2 1.1.1.3 1.1.1.1 TCP Reset 2.2.2.2 2.2.2.3

  32. Towards Trapping Wily Intruders in the Large Inverse Mapping (Successful routing) 1.1.1.2 1.1.1.3 TCP Reset 1.1.1.1 2.2.2.2 2.2.2.3

  33. Towards Trapping Wily Intruders in the Large Inverse Mapping (Successful routing) 1.1.1.2 1.1.1.3 No Response 1.1.1.1 2.2.2.2 2.2.2.3

  34. Towards Trapping Wily Intruders in the Large Inverse Mapping (Unsuccessful routing) 1.1.1.2 1.1.1.3 1.1.1.1 ACK from 1.1.1.4 2.2.2.2 2.2.2.3

  35. Towards Trapping Wily Intruders in the Large Inverse Mapping (Unsuccessful routing) 1.1.1.2 1.1.1.3 1.1.1.1 TCP Reset 2.2.2.2 2.2.2.3

  36. Towards Trapping Wily Intruders in the Large Inverse Mapping (Unsuccessful routing) 1.1.1.2 1.1.1.3 1.1.1.1 ICMP No Route to Host 2.2.2.2 2.2.2.3

  37. Towards Trapping Wily Intruders in the Large So, now that we know what we’re looking for, how do we find it? Let’s just use some simple math – isolate patterns with least-squares curve fitting, and find corelations between network traffic.

  38. Towards Trapping Wily Intruders in the Large

  39. Towards Trapping Wily Intruders in the Large Tracing an attack

  40. Towards Trapping Wily Intruders in the Large • This system does not rely on specific types of attack/patterns/signatures, and does not attempt to reconstruct a detailed transaction log, relying only on statistics. • Can traceback the flow of the attack

More Related