detection of sybil attack in mobile adhock networking

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DETECTION OF SYBIL ATTACKS IN MANET’s MUNNA KUMAR PRASAD (100105609020) PRAKASH KUMAR (100105609026) RAMESH.G (110405609003) SADAM.S (110405609004) PRESENTED BY : PROJECT GUIDE : Mr. A.N.KARTHIKEYAN M.E., Asst. Prof/CSE Dept

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Page 1: DETECTION OF SYBIL ATTACK IN MOBILE ADHOCK NETWORKING

DETECTION OF SYBIL ATTACKS IN MANET’s

MUNNA KUMAR PRASAD (100105609020) PRAKASH KUMAR (100105609026) RAMESH.G (110405609003) SADAM.S (110405609004)

PRESENTED BY :PROJECT GUIDE :

Mr. A.N.KARTHIKEYAN M.E.,Asst. Prof/CSE Dept

Page 2: DETECTION OF SYBIL ATTACK IN MOBILE ADHOCK NETWORKING

AIM OF THE PROJECT

To Detect The New Identities Of Sybil Attackers Using Centralized Base Station and without Any Extra Hardware, Such As Directional Antennae Or A Geographical Positioning System(GPS).

It is able to demonstrate that the proposed scheme detects Sybil identities with good accuracy even in the presence of mobility.

Page 3: DETECTION OF SYBIL ATTACK IN MOBILE ADHOCK NETWORKING

EXISTING SYSTEM A Sybil attacker can either create more than one identity on a single

physical device in order to launch a coordinated attack on the network.

DISADVANTAGES Overhead of packet loss. Low level network performance.

PROPOSED SYSTEM hackers cannot act as source, because one centralized server is

maintaining to check authentication of source. Our proposed system used the NDD (Neighbor discover distance)

Algorithm.

ADVANTAGES To reduce the packet delay and detect the attacker. Data delivery quickly from source to destination. Efficient data transmission on network. Without any loss data will be send in destination.

Page 4: DETECTION OF SYBIL ATTACK IN MOBILE ADHOCK NETWORKING

MODULES:-

1.WIRELESS NETWORK CONFIGURATION SETTINGIt request the ip address of source ,selecting the path, then

attach the file which we want to send and finally request ip address of the destination.

2.TOPOLOGY DESIGNIn topology design all nodes are placed at the particular

distance from each other.3.NEIGHBOR DISCOVERY DISTANCE Each node should know the address of their neighbor nodes.4.SYBIL ATTACK

It create more than one identity of a single physical device in order to weaken the detection process.

Page 5: DETECTION OF SYBIL ATTACK IN MOBILE ADHOCK NETWORKING

1.WIRELESS NETWORK CONFIGURATION SETTING

First the system request the ip address of source node.Then select the path in which node we are sending the

packets.Now the system requests the ip address of destination

node.Source node will decide the path according to the

Received signal strength(RSS).Finally the secure communication takes places.

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2.TOPOLOGY DESIGN

In Topology design all node place at particular distance.The sink hole is at the center of the circular sensing area.Sink hole only decide the path for the packet

transmission.Based on the energy level the sink node will decide the

trusted or untrusted node.It allow the quick data transmission from source to

destination based on energy level of nodes.

Page 10: DETECTION OF SYBIL ATTACK IN MOBILE ADHOCK NETWORKING
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3.NEIGHBOR DISCOVERY DISTANCE(NDD)

NDD is the process which determines the total number and identity of other nodes in its neighbour.

It is a fundamental building block of many protocols including localization routing and group management.

Neighbour discovery is especially important to the proper functioning of wireless networks.

It may cooperate in the performance of various tasks including communications, sensing and localization.

Each node will know the address of their neighbor nodes.

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4.SYBIL ATTACK

It create more than one identity of a single physical device in order to weaken the detection process.

A single attacker could pretend nodes to report the existence of a false bottleneck in traffic.

MANETs are mainly related to illegally gathering sensitive information about mobile nodes.

To relate between a source and its destination, effect on data and transmission time on network.

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CONCLUSIONWe also showed the various factors affecting the detection

accuracy, such as network connections, packet transmission rates, node density, and node speed.

The simulation results showed that our scheme works better even in mobile environments and can detect both join-and-leave and simultaneous Sybil attackers with a high degree of accuracy.

FUTURE ENHANCEMENTOur future work includes tackling issues related to

variable transmit powers and masquerading attacks in the network.