13-09-2012, 04:10 PM
CHANNEL-AWARE DETECTION OF GRAY HOLE ATTACKS IN WIRELESS MESH NETWORKS
[attachment=33732]
INTRODUCTION
Wireless Mesh Networks (WMN)
A multi-hop wireless communication among different nodes
Nodes are dynamically self-organized and self-configured
Advantages-Flexibility, Adaptability, Reconfigurable
architecture
WMNs consist of two kinds of nodes:
Mesh routers
Mesh clients
Denial of Service Attacks in Network layer of WMNS
Rushing attacks
Worm hole attacks
Black hole attacks
Gray hole attacks
Sybil attacks
Prior Works on Selective Forwarding Attacks
1. multipath forwarding
By Karlof et al.
Proposed selective forwarding attacks
Multipath forwarding
Fails to suggest a method to detect and isolate the
attackers from the network
2.CHEMAS algorithm
Proposed by Xiao
Use check point nodes to detect malicious node
Disadvantages
- Increased overhead
- Assumes that the channel is perfect and any packet loss
is due to the presence of malicious nodes.
CONCLUSION
The algorithm utilizes the methodologies of channel estimation and upstream/downstream traffic monitoring to discriminate the selective dropping attack from the estimated normal loss rates.
[attachment=33732]
INTRODUCTION
Wireless Mesh Networks (WMN)
A multi-hop wireless communication among different nodes
Nodes are dynamically self-organized and self-configured
Advantages-Flexibility, Adaptability, Reconfigurable
architecture
WMNs consist of two kinds of nodes:
Mesh routers
Mesh clients
Denial of Service Attacks in Network layer of WMNS
Rushing attacks
Worm hole attacks
Black hole attacks
Gray hole attacks
Sybil attacks
Prior Works on Selective Forwarding Attacks
1. multipath forwarding
By Karlof et al.
Proposed selective forwarding attacks
Multipath forwarding
Fails to suggest a method to detect and isolate the
attackers from the network
2.CHEMAS algorithm
Proposed by Xiao
Use check point nodes to detect malicious node
Disadvantages
- Increased overhead
- Assumes that the channel is perfect and any packet loss
is due to the presence of malicious nodes.
CONCLUSION
The algorithm utilizes the methodologies of channel estimation and upstream/downstream traffic monitoring to discriminate the selective dropping attack from the estimated normal loss rates.