intrusion detection and forensics for self-defending wireless networks

27
Yan Chen Lab for Internet and Security Technology (LIST) Dept. of Electrical Engineering and Computer Science Northwestern University http://list.cs.northwestern.edu Intrusion Detection and Forensics for Self- defending Wireless Networks

Upload: jonah

Post on 04-Jan-2016

40 views

Category:

Documents


0 download

DESCRIPTION

Intrusion Detection and Forensics for Self-defending Wireless Networks. Yan Chen Lab for Internet and Security Technology (LIST) Dept. of Electrical Engineering and Computer Science Northwestern University http://list.cs.northwestern.edu. The Spread of Sapphire/Slammer Worms. - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: Intrusion Detection and Forensics for Self-defending Wireless Networks

Yan ChenLab for Internet and Security Technology (LIST)

Dept. of Electrical Engineering and Computer Science

Northwestern University

http://list.cs.northwestern.edu

Intrusion Detection and Forensics for Self-defending Wireless

Networks

Page 2: Intrusion Detection and Forensics for Self-defending Wireless Networks

The Spread of Sapphire/Slammer Worms

Page 3: Intrusion Detection and Forensics for Self-defending Wireless Networks

The Current Threat Landscape of Wireless Networks

• Wireless networks, crucial for GIG, face both Internet attacks and their unique attacks– Viruses/worms: e.g., 6 new viruses, including Cabir

and Skulls, with 30 variants targeting mobile devices– Botnets: underground army of the Internet, emerging

for wireless networks

• Big security risks for wireless networks– Few formal analysis about wireless network protocol

vulnerabilities – Existing (wireless) IDSes only focus on existing attacks

» Ineffective for unknown attacks or polymorphic worms

– Little work on attack forensics» E.g., how to identify the command-and-control (C&C) channel

of botnets?

Page 4: Intrusion Detection and Forensics for Self-defending Wireless Networks

Self-Defending Wireless Networks

• Proactively search of vulnerability for wireless network protocols– Intelligent and thorough checking through combo of

manual analysis + auto search with formal methods– First, manual analysis provide hints and right level of

abstraction for auto search– Then specify the specs and potential capabilities of

attackers in a formal language TLA+ (the Temporal Logic of Actions)

– Then model check for any possible attacks

• Defend against emerging threat – Worm: network-based polymorphic worm signature

generations– Botnet: IRC (Internet relay chat) based C&C

detection and mitigation

Page 5: Intrusion Detection and Forensics for Self-defending Wireless Networks

Outline• Threat landscape and motivation• Our approach• Accomplishment of this year

– Vulnerability analysis of Mobile IPv6 protocols

– Polymorphic worm signature generation

• Plan for the next year

Page 6: Intrusion Detection and Forensics for Self-defending Wireless Networks

Accomplishments This Year (I)• Intelligent vulnerability analysis

– Focused on outsider attacks, i.e., w/ unprotected msgs– Checked the complete spec of 802.16e before

authentication» Found some vulnerability, e.g., for ranging (but needs to

change MAC)

– Checked the mobile IPv4/v6» Find an easy attack to disable the route optimization of MIPv6 !

– Partnered with Motorola, very interested in the vulnerability found

• Automatic polymorphic worm signature generation systems for high-speed networks– Fast, noise tolerant w/ proved attack resilience– Talking with Cisco IPS group for tech transfer– Patent filed

Page 7: Intrusion Detection and Forensics for Self-defending Wireless Networks

• Six conference, one journal papers and a book chap

– Honeynet-based Botnet Scan Traffic Analysis, invited book chapter for Botnet Detection: Countering the Largest Security Threat

– Detecting Stealthy Spreaders Using Online Outdegree Histograms, in the Proc. of the 15th IEEE International Workshop on Quality of Service (IWQoS), 2007 (26.6%).

– Hamsa: Fast Signature Generation for Zero-day Polymorphic Worms with Provable Attack Resilience, to appear in IEEE Symposium on Security and Privacy, 2006 (9%).

– Towards Scalable and Robust Distributed Intrusion Alert Fusion with Good Load Balancing, in Proc. of ACM SIGCOMM Workshop on Large-Scale Attack Defense 2006(33%).

– Automatic Vulnerability Checking of IEEE 802.16 WiMAX Protocols through TLA+, in Proc. of the Second Workshop on Secure Network Protocols (NPSec) (33%).

– A DoS Resilient Flow-level Intrusion Detection Approach for High-speed Networks, to appear in IEEE International Conference on Distributed Computing Systems (ICDCS), 2006 (14%).

– Reverse Hashing for High-speed Network Monitoring: Algorithms, Evaluation, and Applications, Proc. of IEEE INFOCOM, 2006 (18%). Full version to appear in ACM/IEEE Transaction on Networking.

Accomplishments This Year (II)

Page 8: Intrusion Detection and Forensics for Self-defending Wireless Networks

Mobile IPv6 (RFC 3775)

• Provides mobility at IP Layer

• Enables IP-based communication to continue even when the host moves from one network to another

• Host movement is completely transparent to Layer 4 and above

Page 9: Intrusion Detection and Forensics for Self-defending Wireless Networks

Mobile IPv6 - Entities

• Mobile Node (MN) – Any IP host which is mobile

• Correspondent Node (CN) – Any IP host communicating with the MN

• Home Agent (HA) – A host/router in the Home network which:– Is always aware of MN’s current location– Forwards any packet destined to MN– Assists MN to optimize its route to CN

Page 10: Intrusion Detection and Forensics for Self-defending Wireless Networks

Mobile IPv6 - Process

• (Initially) MN is in home network and connected to CN

• MN moves to a foreign network:– Registers new address with HA by sending Binding

Update (BU) and receiving Binding Ack (BA)– Performs Return Routability to optimize route to CN

by sending HoTI, CoTI and receiving HoT, CoT– Registers with CN using BU and BA

Page 11: Intrusion Detection and Forensics for Self-defending Wireless Networks

Mobile IPv6 in Action

Home AgentCorrespondent

Node

Home Network

Foreign Network

InternetMobile Node

Mobile Node

HA

– MN

TunnelBU

BAHoTI

HoTI

CoTI

HoT

HoT

CoT

BU

BA

Page 12: Intrusion Detection and Forensics for Self-defending Wireless Networks

Mobile IPv6 Vulnerability

• Nullifies the effect of Return Routability• BA with status codes 136, 137 and 138

unprotected• Man-in-the-middle attack

– Sniffs BU to CN– Injects BA to MN with one of status codes above

• MN either retries RR or gives up route optimization and goes through HA

Page 13: Intrusion Detection and Forensics for Self-defending Wireless Networks

MIPv6 Attack In ActionMN HA AT CN

HoTI

HoTI

CoTI

CoT

HoTHoT

Start Return

Routability

Restart Return

Routability

Silently Discard

Bind Ack

Bind Update (Sniffed by AT along the way)

Bind Ack Spoofed by AT

Bind Ack

• Only need a wireless network sniffer and a spoofed wired machine (No MAC needs to be changed !)

• Bind ACK often skipped by CN

Page 14: Intrusion Detection and Forensics for Self-defending Wireless Networks

MIPv6 Vulnerability - Effects

• Performance degradation by forcing communication through sub-optimal routes

• Possible overloading of HA and Home Link• DoS attack, when MN repeatedly tried to

complete the return routability procedure • Attack can be launched to a large number of

machines in their foreign network– Small overhead for continuously sending spoofed

Bind ACK to different machines

Page 15: Intrusion Detection and Forensics for Self-defending Wireless Networks

TLA Analysis and Experiments

• With the spec modeled in TLA, the TLC search gives two other similar attacks w/ the same vulnerability– Complete the search of vulnerabilities w/

unprotected messages

• Implemented and tested in our lab– Using Mobile IPv6 Implementation for Linux (MIPL)– Tunnel IPv6 through IPv4 with Generic Routing

Encapsulation (GRE) by Cisco– When attack in action, MN repeatedly tried to

complete the return routability procedure – DOS attack !

Page 16: Intrusion Detection and Forensics for Self-defending Wireless Networks

Outline• Threat landscape and motivation• Our approach• Accomplishment of this year

– Vulnerability analysis of Mobile IPv6 protocols

– Polymorphic worm signature generation

• Plan for the next year

Page 17: Intrusion Detection and Forensics for Self-defending Wireless Networks

Deployment of SDWN• Attached to a switch connecting BS as a black box• Enable the early detection and mitigation of global

scale attacks• Significantly more challenging compared w/ host-based

IDS/IPS– Huge data volume and lack of host-level information

Original configuration SDWN deployed(a)

(b)

Router/switch

Internet

802.1x

BS

Users

802.1x

BS

Users

Switch/BS controller

Internet

sca

n

po

rtS

DW

Nsy

ste

m

802.1xBS

Users

802.1xBS

Users Honeynet

SDWN

system

Gateway

Page 18: Intrusion Detection and Forensics for Self-defending Wireless Networks

Automatic Length Based Worm Signature Generation

• Majority of worms exploit buffer overflow vulnerabilities

• Worm packets have a particular field longer than normal

• Length signature generation– Parse the traffic to different fields– Find abnormally long field– Apply a three-step algorithm to determine a

length signature– Length based signature is hard to evade if the

attacker has to overflow the buffer.

Page 19: Intrusion Detection and Forensics for Self-defending Wireless Networks

Length Based Signature Generator

Filter

SuspiciousTraffic Pool

NormalTraffic Pool

YESQuit

SignaturesLESGCore

ProtocolSpecification

ParsedNormal

ParsedSuspicious

ProtocolParser

NO

Pool sizetoo small?

Page 20: Intrusion Detection and Forensics for Self-defending Wireless Networks

Evaluation of Signature Quality

• Seven polymorphic worms based on real-world vulnerabilities and exploits from securityfocus.com

• Real traffic collected at two gigabit links of a campus edge routers in 2006 (40GB for evaluation)

• Another 123GB SPAM dataset

Page 21: Intrusion Detection and Forensics for Self-defending Wireless Networks

Outline• Threat landscape and motivation• Our approach• Accomplishment• Achievement highlight: a Mobile IPv6

vulnerability• Plan for the next year

– Insider attack analysis– Complete the polymorphic worm signature

generation– Intrusion forensics for botnet command and

control channel detection

Page 22: Intrusion Detection and Forensics for Self-defending Wireless Networks

Insider Attack Analysis • Not hard to become a subscriber• Can five subscribers bring down an entire

wireless network (e.g., WiMAX) ?• Check vulnerability after authentication

• Plan to analyze various layers of WiMAX networks– IEEE 802.16e: MAC layer– Mobile IP v4/6: network layer– EAP layer

Page 23: Intrusion Detection and Forensics for Self-defending Wireless Networks

802.16e SS Init Flowchart

Page 24: Intrusion Detection and Forensics for Self-defending Wireless Networks

Work Done

Page 25: Intrusion Detection and Forensics for Self-defending Wireless Networks

Future work

Page 26: Intrusion Detection and Forensics for Self-defending Wireless Networks

•Proactively secure the wireless networks• Search of network protocol vulnerabili-ties• Automatically detect and filter unknownand/or polymorphic worms• Intrusion forensics and mitigation forbotnet-based attacks

• Intelligent and complete vulnerability search through the combo of manualanalysis & verification via formal methods• Network-based automatic signature generation for polymorphic worms• Botnet command-and-control channeldetection and mitigation

Intrusion Detection and Forensics for Self-defending Wireless

NetworksYan Chen, Northwestern University

Tel. (847) 491-4946, E-Mail: [email protected]

Scientific/Technical Approach Accomplishments• Successfully check for outsider attack vulnerabilities of MIP v4/6 and 802.16e (WiMAX) protocols • Network-based automatic signature generations

Challenges• State space explosion for vulnerability search w/ formal methods• Large amount of traffic to monitor on high-speed links

Switch/BS controller

Internet

sca

n

po

rtS

DW

Nsy

ste

m

802.1xBS

Users

802.1xBS

Users Honeynet

SDWN

system

Gateway

Page 27: Intrusion Detection and Forensics for Self-defending Wireless Networks

Conclusions

• Vulnerability analysis of wireless network protocols: 802.16e and mobile IP specs

• Network-based polymorphic worm signature generation for self-defending wireless networks

Thank You !