Abstract nasty nodes that show the same opinion to

Abstract – Since
an ad hoc network is a collection of infrastructure less & wireless mobile
nodes, which act as a host as well as a router. Communication among nodes takes
place in hop-to-hop fashion without a centralized administration. AODV is well-known
on-demand reactive routing protocols for mobile ad hoc networks. But in
existing AODV, there is lack of sufficient security provision against
well-known attack “Black hole attack”. Black hole nodes are those nasty nodes
that show the same opinion to forward packet to destination but do not forward
packet intentionally. This Paper presents a watch-dog mechanism for the AODV
routing protocol to identify such misbehavior based on promiscuous listening. This
method firstly notices a black hole node and then gives a fresh route avoiding this
node. In lightly loaded, aggressive situation, our method gives better throughput
as compared to a defenseless AODV protocol.

  Key terms – Mobile Ad hoc networks,
routing, security, AODV, black hole attack, Prevention.

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I.                   
Introduction

It is well known that there has
been fantastic growth in the use of wireless communication over the last few
years, from satellite transmission to home personal area networks
(PANs-Bluetooth etc.). One side is advantages of wireless to transmit data
among users in a common area while remaining mobile another side is the
disadvantages of vulnerability. Nevertheless the range of transmitters or their
nearness to wireless access points restricts distance between participants. Ad
hoc networks moderate this problem by allowing out of range nodes to route data
through intermediate nodes.

Ad hoc networks have a wide collection of
military, commercial & educational applications and other emergency and
disaster situations. Ad hoc networks are ideal in situations where installation
of an infrastructure is not possible because the infrastructure is too
expensive or too vulnerable, the network is to temporary, or the infrastructure
was destroyed. A sensor network, which consists of several thousand small
low-powered nodes with sensing capabilities, is one of the advanced
applications of MANET’s. Clearly, security is a vital issue in such areas.

 

   However,
recent wireless research indicates that the wireless MANET presents a large
security problem than

 

 

conventional wired and wireless networks. While
most of underlying features make MANET’s useful and popular.

First, all signals go through bandwidth-constrained wireless links in a
MANET, which makes it more prone to physical security threats than flexible
landline networks. Possible link attacks range from passive eavesdropping to
active interference. Second, mobile
nodes are roaming independently and are able to move in any direction. In this
case denial of service (DOS) can
easily be launched if a malicious node floods the network with fake routing
message. The other nodes may unknowingly propagate the messages. Third, decentralized decision making in the MANET relies on the
cooperative participation of all nodes. The malicious node could simply block
or modify the traffic traversing it by refusing cooperation to break the
cooperative algorithm. Finally, an attacker could create a new type of DoS
attack by forcing a node to replay packets to exhaust its energy.

In general, the wireless MANET is particularly
vulnerable due to its elementary feature of open medium, dynamic topology, and
absence of central authorities, distributed cooperation, and constrained
capability. The existing security mechanisms for wired networks cannot be frankly
applied in wireless MANET’s.

Theoretically there may be several type of
attacks are possible but generally in practice Two types of attacks occurs first
is passive attacks in which a node is
driven its selfishness and active attacks
in which a malicious node has the goal of interrupting normal network
operation. Although a malicious node can deploy a variety of DoS attacks 1,
2, we only consider the attacks caused by the failing to perform packet
forwarding while participating in routing. This problem is called as the black
hole problem. Simulation in 3 shows that if 10%-40% of the nodes fail to
forward packets (but participate in the routing protocol), this can cause a
throughput degradation of about 16%-32%.

In this paper, we propose a mechanism based on
promiscuous listening to detect misbehaving nodes. For a given node, the ratio
between the number of dropped data packets and the number of successfully
forwarded data packets by the node represents a metric to mark the node as
either misbehaving or well behaving. If this ratio exceeds a threshold, the
node is marked as misbehaving. If the ratio is below the threshold, the node is
marked as well behaving. Upon detecting a misbehaving node, the detecting node
tries to avoid the misbehaving node and route the packets along another path.
This decision has been taken locally informing neither the sender nor the
receiver, that is the misbehaving nodes can be avoided transparently from the
sender and the receiver.

The remaining of this paper goes as follows. In
section2, we investigate some of currently proposed solutions for the routing misbehavior problem in ad hoc
networks. Section 3, presents our watch-dog mechanism. Results from simulation
using Network Simulator 2 (NS2) are presented in section 4. Section 5 concludes
the paper.

 

 

II.                 
Related Research Work

In this section, we survey some of the current
attempts at solving the problem of routing misbehavior in ad hoc networks.

Sergio Marti 3 introduced Watchdog and Path
rater techniques with Dynamic source Routing (DSR) 4 that improve throughput
in a MANET by identifying misbehaving nodes that agree to forward packets but
never do so. Watchdog is used to identify misbehaving nodes, and Path rater to
help routing protocol to avoid these nodes.

The CONFIDANT scheme 5 utilizes the concept of
reputation. Each node keeps track of a black-list of misbehaving nodes.
Detection of a misbehaving neighbor and/or reception of a warning message from
trusted peers against a node would add the misbehaving node to the black-list.
A node will not service a request coming from a black-listed node. Also a
packet is routed so that to avoid black-listed nodes in its path. Reliance on
trust, the ability of malicious nodes to blackmail a legitimate node and the un-scalability
of the global distribution of the black-list are some limitations of this
scheme.

H.Deng, W.Li and D.P.Agrawal 6 proposed a
solution for single black hole problem for ad hoc on-demand distance routing
protocol. In this method source node do not send packet to the destination node
after receiving the route reply packet, but source node finds one or more route
to the intermediate node that replays the RREQ message to check whether the
route from the intermediate node to the destination node exits or not. This
methods increases the routing overhead and is only solves the problem of single
black hole node.

In CORE scheme 7, each node keeps track of
reputation values of its neighbors only. The scheme uses more complex
reputation systems. A node attains a negative reputation only when its neighbor
detects its misbehavior and this negative value is kept local to the detecting
neighbor. A misbehaving node will eventually be isolated from the network when
all its neighbors detect its misbehavior and thus stop forwarding packets
to/from it. With mobility in mind, one would expect this mechanism to fail if
the misbehaving node’s neighbors continuously change allowing for a new chance
for the malicious node to drop more packets. The authors did not present
information on the performance of this scheme. It should be noted that all the
above schemes fail in the case of multiple colluding nodes. For example, for
this scheme if two colluding nodes are neighbors, one of them would behave
normally keeping a path through the other node to drop packets.

                    

III.              
The AODV Watch Dog Algorithm

A.              
AODV Routing Protocol

There are three types of routing messages in the
Ad hoc On-demand Distance Vector (AODV) 8 routing protocol:  Route Request (RREQ), Route Reply (RREP) and
Route Error (RERR). AODV adopts a proactive scheme to establish routes among
nodes. If node A wants to communicate with another node B and it has no active
route to it, it issues a RREQ message for node B. The RREQ message contains the
address of B, the address of A, a sequence number unique per node per RREQ
message, and the number of hops traversed by the RREQ message so far. Node A
broadcasts the RREQ message. Upon reception of an RREQ message, a neighboring
node C checks to see if it has an active route to B. If it does, it replies to
node A with an RREP messages containing the address of node B, the number of
hops (as the routing metric) to B and a sequence number for the route. If node
C does not have an active route to B, it either creates or updates its route to
A using the information it gets from the RREQ message. Node C then broadcasts
the RREQ message after incrementing the message’s number of traversed hops. If
the RREQ message reaches the destination B, B issues an RREP message containing
its current sequence number and uni-cast it to the source of the RREQ. Each
intermediate node on the path that the RREP message traverses to A creates a
route to B if it does not have one, and forwards the RREP message using its route
to A. If it has an active route to B, the intermediate node examines the RREP’s
sequence number and number of hops. A node updates its route if the new route
has a larger sequence number or it has the same sequence number but with less
number of hops. It then forwards the RREP message. Otherwise, the node drops
the RREP message. When node A receives the RREP message, it creates a route to
B using the fields in the RREP message.

Each node maintains a routing table containing
an entry for each destination it knows about. An AODV routing table entry
contains the destination node address, the address of the next hop, the number
of hops to reach the destination via this route, and the destination’s sequence
number associated with this route. AODV has two modes of route maintenance:
periodic hello messages and link layer feedback. In the former, nodes exchange
hello messages periodically. The absence of a specified number of consecutive
hello messages indicates that a node is either down or out of wireless range. A
link layer feedback is generated in case of a missing ACK or a missing CTS
message after a specified number of retries. Either of these conditions causes
a node to either try a local route repair by sending an RREQ message if the
node is closer to the destination than the source or to broadcast an RERR
message containing the broken node address and, in the case of link layer
feedback, the destination’s address that the node was trying to reach. Each
node receiving this RERR message will bring down its route to the mentioned
destination if the route goes through the source of the RERR message and
broadcast the RERR message if there are nodes that use this route. For each
routing table entry, each node keeps a precursor list of upstream nodes using
the route entry. Finally, each routing table entry expires after some specified
amount of time if it was not used for this time.

 

B.              
Routing Attack(Black Hole
Attack)

Black hole
attack 6 is an active insider attack; the attacker consumes the intercepted
packets without any forwarding

 

 

 

Figure 1: The Black hole problem

 

Based on
original AODV protocol, any intermediate node may respond to the RREQ message
if it has fresh enough route, which is checked by the destination sequence
number contained in the RREQ packet. In the above figure node 1 is source node
where as node 4 is destination node. Source node broadcasts route request
packet to find a route to destination node. Here node 3 acts as black hole.
Node 3 also sends a route reply packet to the source node. But a route reply
from node 3 reaches to source node before any other intermediate node. In this
case source node sends the data packet to destination node through node 3. But
as the property of black hole node, the very node does not forward further and
dropped it. But source node is not aware of it and continues to send packet to
the node 3. In this way the data, which have to be reached to the destination
fails to reach there? There is no way to find out such kind of attack. These
nodes can be in large number in a single MANET, which makes the situation more
critical. 

 

C.             
The Watch-dog Mechanism

In my proposed
solution, each node maintains two tables, one is called pending packet table
and another one is called node-rating table. In pending packet table, each node
keeps track of the packets it sent. It contains a unique packet ID, the address
of the next hop to which the packet was forwarded, address of the destination
node, and an expiry time after which a still-existing packet in the buffer is
considered not forwarder by the next hop.

In node rating table, each node
keeps rating of nodes, which are adjacent to it (means nodes are within its
communication range). This table contains the node address, a counter of
dropped packets observed at this node and a counter of successfully forwarded
packets by this node. The fourth field of the above node rating table is
calculated by the ratio of data forwarding failure and successfully forwarded
packets, if this ratio is greater than a given threshold value then this node
misbehave value will be 1(means it is considered as a misbehave node),
otherwise it is considered as a valid node. An expired packet in the pending
packet table causes the packet drops counter to increment for the next hop
associated with the pending packet table entry.

Each node listens to packet that
are within its communication range, and only to packets belonging to its
domain. Then it verifies each packet and prevent forged packet. If it observes
a data packet in its pending packet table, then it removes this data packet
from pending packet table after authenticating the packet. If it observes a
data packet that exits in its pending packet table with source address
different from the forwarding node address, then it increments the packet
forwarding value in the node-rating table.

For deciding whether a node is
misbehaving or act as a legitimate one, depend on the selection of threshold
value. For example if we take a threshold value of 0.2. This means that as long
a misbehaving node is forwarding twice packets as it drops it will not be
detected. If we take a lower value of threshold then it will increase the
percentages of false positives. After detecting a misbehaving node, a node will
try to do local repair for all routes passing through this misbehaving node. If
local repair process fails, then it will not send any RERR packet upstream in
the network. This process tries to prevent a misbehaving node from dropping
packets, and also prevent black-mailing of legitimate nodes. To avoid
constructing routes, which traverse misbehaving nodes, nodes drop/ignore all
RREP messages coming from nodes currently marked as misbehaving. To stop
misbehaving node to act actively in a network, the entire packet originating
from this node has been dropped as a form of punishment.

 

IV.               
The Results

     We use the NS2 9, 10 simulator
to build a module for our AODV watch-dog mechanism. The module inherits from
the AODV module already integrated in NS2. It adds the two tables: the pending
packet buffer and the node ratings table. It also uses the support to tap MAC
layer packets. The number of nodes simulated is 50 nodes moving in an area of 2000×1000
meters squared with speed between 0 and 10 m/s and using the random waypoint
mobility model. Each simulation run is for 1000 seconds. We vary the pause
times of the nodes between 0 seconds (high mobility), 100 seconds, 200 seconds,
300 seconds, 400 seconds, 500 seconds (medium mobility), 600 seconds, 700
seconds, 800 seconds, 900 seconds and 1000 seconds (low mobility). We use CBR
traffic generators with 16 packets/second and 512 bytes packet size. We use 10
number of CBR traffic sources. Finally, we vary the number of misbehaving nodes
between 0, 3 and 5 nodes. We measure the throughput, the total number of
received packet per unit time. We also measure the packet delivery ratio, the
ratio between the number of packets received by the CBR sink at the final
destination and the number of packets originated by the CBR sources.

The throughput and packet delivery ratio (PDR) at different pause times
and different number of misbehaving nodes has been measured when the number of
CBR sources is 10. For a lightly loaded network, the effect of the watch-dog
mechanism is to improve the throughput and packet delivery ratio in the
existence of misbehaving nodes, while retaining the approximately same
throughput and packet delivery ratio as the defenseless AODV in the case of 0
misbehaving nodes.

 

 

V.                 
Conclusion

The mobile Ad hoc Network is an emerging
research area with practical application, but they are vulnerable in many
settings to nodes that misbehave when routing packets.

In general, routing security in wireless
networks appears to be a nontrivial problem that cannot easily be solved. It is
impossible to find a general idea that can work efficiently against all kinds
of attack, since every attack has its own distinct characteristics.

In this paper we analyze extension to AODV to
mitigate the effect of routing misbehavior in ad hoc networks- the watch-dog
mechanism. We show that this technique increases throughput by 16% to 20% and
packet delivery ratio by 8% to 20% in the presence of 8% misbehaving nodes in a
network with moderate mobility.