1. A Secure Ad-hoc Routing Approach using Localized Self-healing Communities
MobiHoc, 2005
Presented by An Dong-hyeok
CNLAB at KAIST

2. Community-based secure routing protocol Analytic model Simulation
Contents
Introduction
Problem statement
Community-based secure routing protocol
Analytic model
Simulation
Conclusions 2
CNLAB at KAIST
CALAB at KAIST

3. 1. Introduction Introduction Mobile ad hoc networks(MANETs)
Vulnerable to routing attacks( especially attacks launched by non-cooperative network members )
Packet loss is common
Security threats about routing have not been fully addressed 3
A new intrusion protection mechanism, community-based security
Suggest the “self-healing community”
From node-to-node delivery to community-to-community
Solution
CNLAB at KAIST

4. 2. Problem statement Benefits
RREQ flooding attack by non-cooperative members
(selfish or intruded member nodes)
Direct RREQ floods
Non-cooperative members continuously generate RREQ
RREQ rate limited & packet suppression needed 4
Indirect RREQ floods
RREP & DATA packet loss
Indirectly trigger more RREQ floods
Excessive floods deplete network resource
CNLAB at KAIST

5. dest source RREQ RREP 2. Problem statement (Indirect attack example)
Benefits
2. Problem statement (Indirect attack example)
RREQ 5
dest
source
RREP
RREQ forwarding
Can trigger more RREQ floods initiated by other good nodes
RREP & DATA packet loss is common in MANET
Hard to differentiate attackers from non-attackers
- network dynamics? non-cooperative behaviors?
CNLAB at KAIST

6. 3. Community-based secure routing protocol
Technology
3. Community-based secure routing protocol
3.1 Network assumptions
Assumption 1
A node can always monitor ongoing transmissions even if the node itself is not the intended receiver 6
Assumption 2
Radio transmission is omni-directional and radio links are symmetric
Assumption 3
In a network locality there are redundant network members with high probability
CNLAB at KAIST

7. 3. Community-based secure routing protocol
Technology
3. Community-based secure routing protocol
3.2 Network security assumptions
Assumption 1
All packet transmissions (including control, data packets and their ACKs) are protected by data origin authentication service.
Every packet is authenticated and the packet sender’s identity is unforgeable 7
Assumption 2
The ad hoc nodes are equipped with hardware needed by packet leashes or Brands-Chaum protocols[6]
Any pair of topological neighbors in ad hoc routing are physical neighbors
CNLAB at KAIST

8. 3. Community-based secure routing protocol
Technology
3. Community-based secure routing protocol
3.3 Self-healing community (2-hop scenario)
Area defined by intersection of 3 consecutive transmissions
Node redundancy is common in MANET
Not unusually high, need 1 “good” node inside the community area 8
Community leadership is determined by contribution
Leader steps down (being taken over) if not doing its job (doesn’t forward within a timeout)
Community member
Community member must be in the transmission range of exactly three RREP forwarders
CNLAB at KAIST

9. B C D Community 3. Community-based secure routing protocol
Technology
3. Community-based secure routing protocol
3.3 Self-healing community (2-hop scenario)
Community 9 B C D
CNLAB at KAIST

10. dest source Communities 3. Community-based secure routing protocol
Technology
3. Community-based secure routing protocol
3.4 Self-healing community (multi-hop scenario)
Communities
source
dest
1010
The concept of “self-healing community” is applicable to multi-hop routing
CNLAB at KAIST

11. Community around V formed upon hearing RREP
Technology
3. Community-based secure routing protocol
3.4 on-demand initial configuration
Community around V formed upon hearing RREP
RREQ
upstream
1111 V1 U V E V2
RREP EV
CNLAB at KAIST

12. Communities (if C forwards a correct RREP)
Technology
3. Community-based secure routing protocol
Communities (if C forwards a correct RREP) C”
1212
Communities(C’ wins) D E B C
dest
source C’
CNLAB at KAIST

13. source dest PROBE PROBE_REP X no ACK
Technology
3. Community-based secure routing protocol
3.4 reconfiguration of self-healing community (multi-hop scenario)
PROBE
PROBE_REP
1313
source
X no ACK
dest
CNLAB at KAIST

14. 4. Analytic model 4.1 mobile network model Technology
Divides the network into large number n of very small tiles
A node’s presence probability P at each tile is small
A spatial binomial distribution B(n, p) 14
When n is large and P is small, B(n, p) is approximately a spatial Poisson distribution with rate
If there are N mobile nodes roaming i.i.d
The probability of exactly k nodes in an area A’
CNLAB at KAIST

15. 4. Analytic model 4.2 Community area Aheal Technology 15
(left) maximal community
2-hop RREP nodes are
Area approaching
(right) minimal community
2-hop RREP nodes are
Area approaching 0
CNLAB at KAIST

16. 4. Analytic model 4.3 modeling adversarial presence Technology
Θ: percentage of non-cooperative network members
X: number of nodes in the forwarding community area 16
Y: number of cooperative nodes
Z: number of non-cooperative nodes
CNLAB at KAIST

17. 4. Analytic model 4.4 Effectiveness of CBS routing Technology
Per-hop failure prob. Of community-to-community routing is negligible with respect to network scale N 17
Per-hop success prob. Of node-to-node ad hoc routing schemes is negligible
Tremendous gain EG := 1 / negligible
CNLAB at KAIST

18. Technology
4. Analytic model
4.4 Effectiveness of CBS routing N q 18
It is even more tremendous when either network scale or non-cooperative ratio increases.
CNLAB at KAIST

19. Alternative
4. Simulation
4.1 Performance Gap 19
CBS-AODV’s performance only drops slightly with more non-cooperative behavior
CNLAB at KAIST

20. Alternative
4. Simulation
4.1 Mobility’s impact 20
CNLAB at KAIST

21. Alternative
4. Simulation
4.1 Less RREQ 21
In CBS-AODV, # of RREQ triggered is less sensitive to non-coorperative ratio
CNLAB at KAIST

22. 4. Conclusions Conclusion
Conventional node-to-node routing is vulnerable to routing disruptions
Excessive but protocol-compliant RREQ floods
RREP / DATA packet loss 22
Analytic study approves the community design
The new community-to-community secure routing is solution
More optimal estimation of forwarding window & probing interval
Secure and efficient key management between two communities
Open challenges
CNLAB at KAIST

23. 23
Any Question?
CNLAB at KAIST