distributed security system for mobile ad-hoc … security system for mobile ad-hoc ... based method...

Distributed Security System for Mobile Ad-Hoc Computer

Networks

Ms.Krutika K. Chhajed Dr. M. S. Ali

Department of Computer Science & Engg. Principal,

PRMIT & R, Badnera PRMCEAM, Badnera

Abstract— Ad-hoc wireless networks are increasing in popularity,

due to the spread of laptops, sensor devices, PDAs and other mobile electronic devices. These devices will

eventually communicate with each other and hence there

is a need of security in MANETS.This paper describes the

different types of attacks that are very common i.e. the Distributed Denial of Service attack, the Blackhole attack

and the Wormhole attack, also provide the mechanism to

detect these attacks using the different techniques and the

relative comparison between these three attacks. It provides a comparison of some of the common

parameters on the different nodes in these different types

of attack scenario. So that a novel and optimum solution

can be provided, this can secure the nodes from different types of attacks.

Keyword: MANET, DDoS attack, Blackhole, Wormhole

attack.

INTRODUCTION

Ad-hoc wireless networks are increasing in popularity,

due to the spread of laptops, sensor devices, PDAs and other mobile electronic devices. These devices will

eventually need to communicate with each other.

However there is a need to implement a secure ad hoc

network that might be used in emergency services, disaster assistance, and military applications. The security

includes controls to limit access to the network, in order to

protect it from intruders or unwanted bystanders. Mobile

Ad hoc Networks are the networks formed for a

particular purpose. These networks assume that an end

to end path between the nodes exists. They are often

created on-the-fly and for one-time or temporary use.

They find their use in special applications like military, disaster relief etc that are in a need of forming a new

infrastructure less network with all pre-existing

infrastructure being destroyed. [2]

The basic working of MANETS is such that every node is independently working and only keeping the routing

information with respect to other node, it becomes

difficult for the node to keep track of each and every node

entering and leaving the MANET and hence it becomes very easy for an unintended node to enter into the

MANET and attack the network to disrupt the normal

working. Implementing security in MANET is a

challenging task. Because here node itself will be acting as a router node. So identifying neighbor node as a

legitimate node or malicious node is a difficult thing in

MANET. [3]Thus security of the data is the most important aspect to be handled when dealing with

MANETS.

A Mobile Ad hoc Network (MANET) is a collection of

mobile node connected through wireless links.

[3].The MANETS are different from the traditional

infrastructure based networks in the way that there are

nodes which are mobile. And hence the challenges in such

networks are different from traditional infrastructure based networks.

Security Challenges in MANETS: a) Dynamic Topology: the nodes are moving and may

leave or join the network dynamically. Establishing the trust among the network nodes is difficult.

b) Battery constraints: the nodes are mobile and work

on battery so power consumption must be less.

c) Lack of Central authority: In MANETS there will be no central authority. So to implement security is a

challenging task.

d) Insecure Environment: the nodes are continuously

moving so it is difficult to find out the malicious nodes which can attack and steal the data. [1]

In Ad hoc networks every node act as the sender receiver

and also as a router because it lacks the central authority. The routing protocols are needed for transmitting the data

from source to destination using multiple hops.

There are two basic suggested approaches for

routing in MANETS. These are Topology Based Routing

and Position Based Routing. Topology-based routing

protocols use the information about the links that exist

in the network to perform packet forwarding. They can be

further divided into proactive, reactive, and hybrid

approach Position-based rout ing algorithms eliminate

some of the limitations of topology-based routing by

using additional information. They require that information

about the physical position of the participating nodes be available. Commonly, each node determines its own

position through the use of GPS or some other type

of positioning service. A location service is used by the

sender of a packet to determine the position of the destination and to include it in the packet’s destination

address.

Attacks in MANETS

Table1 gives a few examples of attacks at each layer.

Some attacks could occur in any layer of the network

protocol stack, e.g. jamming at physical layer, hello flood at network layer, and SYN flood at transport layer are all

DoS attacks.

Table 1: Attacks occurring at different layers in protocol stack

Layer Attacks

Application Layer data corruption, viruses and worms

Transport Layer TCP/UDP SYN flood

Network Layer hello flood, blackhole

Data Link Layer monitoring, traffic analysis

Physical Layer eavesdropping, active interference

Krutika K Chhajed et al , International Journal of Computer Science & Communication Networks,Vol 5(3),184-191

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The network layer attack on ad hoc networks can be

broadly classified into two categories one based on source of attacks [17] i.e. External and internal attacks and the

other based on the behavior of attack i.e. active and

Passive attacks.

In external attack, attacker from outside the network tries to get the access to the current network and once it

becomes the part of the network, interrupts the ongoing

transmission and performance. External attacker can flood

network bogus packets in the network to cause congestion in the network. They can be prevented by implementing

the firewalls.

In Internal attack, the attacker node is already

the part of the network, and also contributes in normal network activities, but after some time, it starts with the

malicious behaviour. It is more difficult to detect as

compare to the external attacks.

RELATED WORK

Wei-Shen Lai et al [11] have proposed a scheme to

monitor the traffic pattern in order to alleviate distributed denial of service attacks. This mechanism

adopts the bandwidth allocation policy to assign normal

users to higher priority queue and the suspected attackers

to the lower priority queue. S.A.Arunmozhi, Y.Venkataramani [12] discussed the mechanism of DDoS

attack and proposed the defense scheme to detect the

DDoS attacks. In this scheme the proposed defense

mechanism uses the MAC layer information to detect the attackers. Rizwan Khan, A. K. Vatsa [14] proposed a

clustering based prevention technique for the DDos attacks.

Niresh Sharma, Rajdeep Singh et al [15] proposed the

secure IDS to detect this kind of attack and block it. The algorithm was proposed which uses the Anomaly based

Intrusion detection system which uses different intrusion

detection parameters such as packet reception rate, inter

arrival time. V.Priyadharshini and Dr.K.Kuppusamy [18] proposed a new Cracking algorithm for detection of

DDOS attack.

The term “Blackhole” suggests a node which

absorbs all information passing through it by not forwarding it to the destination node. As a result of the

dropped packets, the amount of retransmission needed

increases leading to congestion. Several schemes have

been proposed for detecting preventing the black hole attack some of the methods can be stated as follows.

H. Deng, W. Li and D. P. Agrawal, [19] have proposed a solution to cope with the black hole attack in

AODV. First, they suggest disabling the ability of an

intermediate node to send a RREP and allow only the

final destination to do that. T hey have proposed another solution which requires that the intermediate node

adds its next hop’s information to the RREP packet before

sending it. B. Sun et al [20] proposed a new scheme to

ascertain the safety of the established path to secure AODV. H. Miranda and L. Rodrigues [21] proposed another

scheme based on reputation system so called Friend and

Foes. This scheme aims to prevent the selfish nodes from disrupting the network operations by refusing to

participate correctly to the forwarding process. E.

Gerhards-Padilla et al [22] proposed a TOGBAD approach

to defend against colluding black hole attack in tactical

MANETs, in which a successful attack can lead to human

life loss. Raj PN et.al [23] discuss a protocol viz.

DPRAODV (Dynamic, Prevention and Reactive AODV)

to counter the Black hole attacks. Unlike normal AODV,

DPRAODV checks to find whether the RREP_Seq_No is

higher than the threshold value. M. Umaparvathi, and D. K Varughese [24] proposes two tiers secure AODV

(TTSAODV) routing protocol which is an extension over

AODV protocol. In tier 1 security, the previous and the

next hop of any intermediate node exchanges the verification messages to verify that the next hop of the

intermediate hop is also having the fresh path to the

destination.Similarly for detecting collaborative black

hole attack, tier 2 protocol is used.Jitendra kumar Rout et al [25] proposed a Secure Fault- Tolerant Paradigm

(SFTP) which checks the Blackhole attack in the network.

The Wormhole Attack was introduced in [26],

[27], [28]. In this an attacker, or potentially multiple colluding attackers, surreptitiously relay packets between

distant locations. This can give a node the impression

that it is the neighbor of a node that is far away. Y. C. Hu

et al [26] introduced Packet Leashes method in which two types of methods have been considered: The

Geographic leashes and the temporal leashes. In

Geographic leashes, node location information is used to

bind the distance a packet can traverse. Lazos L, et al [29] proposed a graph theoretic model to characterize

the wormhole attack and ascertain the necessary and

sufficient conditions for any candidate solution to

prevent wormholes. They used a Local Broadcast Key (LBK) based method to set up a secure ad-hoc network

against wormhole attacks. J. Eriksson et al [30] proposed

a practical countermeasure to the wormhole attack that

presented as an extension to the IEEE 802.11 MAC layer.

The following table summarizes the different techniques

discussed above.

Table 2: Summary of different techniques for Detection and prevention of attacks in MANETS

Sr.

No Author Attack Detection/

Prevention

Method

1

Wei

Shen Lai DDoS Detection

Priority Queue

based schemes

2 S.A.Arun

mozhi DDoS Detection

Status values

from MAC Layer

3 Minda

Xiang DDoS

Mitigation

after attack

Using Load

Protection Node

4 Rizwan

Khan DDoS Prevention Clustering based.

5 Niresh

Sharma

DDoS

Detection

Anomaly Based

Intrusion

detection system

6 Laxmi

Bala

DDoS

Detection &

Prevention

Quality Based

Bottom Up

Detection

7 Dr.K.Ku

ppusamy DDoS Detection

New Cracking

algorithm


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8

H. Den

Blackh

ole

Mitigating

after attack

Allow final

destination to

send RREP

9 B. Sun

Blackh

ole

Mitigate

after attack

Cryptography

based reaction

mechanism

10 H.

Miranda

Blackh

ole Prevention

Reputation based

Friends and Foes

11 E.Padill

a

Blackh

ole Detection

Topology graph

based anomaly

detection

12 Raj PN

Blackh

ole

Detection

and

prevention

DPRAODV

approach

13

M.

Umaparv

athi

Blackh

ole

Prevention

Two tier Secure

AODV approach

14

Jitendra

kumar

Rout et

al

Blackh

ole Detection

Secure Fault

Tolerant

Paradigm

approach

15 Y. C. Hu

et al

Wormh

ole Detection

Packet Leashes

temporal and

Geographic

16 Lazos L,

et al

Wormh

ole Prevention

Graph Theoretic

approach

17

J.

Eriksson

et al

Wormh

ole Prevention

Truelink,

extension to the

802.11 MAC

layer

18 Shang-

Ming

Jen et al

Wormh

ole Detection

Hop count

Analysis scheme

using MHA

algorithm

19

Ritesh

Mahesh

wari,

Wormh

ole Detection

Connectivity

Graph

information

20

Dr. A.

Francis

Devaraj

Wormh

ole

Detection

and

Prevention

Multilayer

detection

approach

PROPOSED SYSTEM

The proposed system consists of three independent modules each of which deals with one of the type of attack

the DDoS, Blackhole and the Wormhole attack. Each of

these modules works independently and creates different

trace files which can then be used to generate comparison

graphs.

The basic work of the system can be shown in Fig.1

below:

Fig 1 : Basic block diagram of the proposed system

Each of the three modules first creates the MANET environment and then simulates the attack in that

environment. After attack simulation the system apply the

technique for detection and detects the attack and register

the values of different parameters of the node in the trace files or the awk files which can be then used for

generation of graphs and studying the behavior of the

system. The basic steps of each of the module can be shown a in the fig 3.2 below.

Fig 2: Basic flow of each of the attack detection

module

a) Design of the module to illustrate the DDoS attack:

The design of the module required for the illustration of

the DDoS attack consists of following basic steps:


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1. Create number of nodes to form a network.

2. Setup the links between these nodes 3. Setup the MANET environment for these nodes.

4. Create files to trace the simulation as well as monitor

queue that stores packet.

5. Start the simulation and note the values in the trace files.

6. Read the trace files in different awk files for different

nodes

7. Generate graphs based on the data at different node before attack and after attack.

b) Design of the module for illustration of Black hole

attack: For the illustration of the black hole attack the algorithm

can be given as follows:

1. Create the patch file for setting the AODV protocol

environment and patch it to the current network simulator environment.

2. Create the nodes and assign the properties to these

nodes relevant to the MANET environment.

3. Set one node as the blackhole node. 4. Simulate the blackhole attack in the simulator using

the tcl file and record the output of the simulation in

the trace file.

5. Read the trace file to check the effect of blackhole attack on the ad hoc network.

c) Design of the module for illustration and detection

of Worm hole attack: The wormhole attack is simulated in the MANET

environment as follows:

1. Create the nodes and set the MANET environment

2. Create the node environment 3. Start the simulation and during the simulation run the

CPP code for the detection of the wormhole attack using

unit disk graph method.

4. Note the contents in the trace files to check the effect of wormhole attack on the network.

The algorithm used for the detection of the wormhole

attack is the Unit Disk Graph algorithm which uses the connectivity graph Information for finding out the

forbidden nodes in the graph and thus detecting that the

attack has occurred.

The Unit Disk Graph algorithm can be stated as

follows:

1. In UDG each node is modeled as a disk of unit radius in

the plane. 2. Each node is a neighbor of all nodes located within its

disk

3. The basic idea in our detection algorithm is to look for

graph substructures that do not allow a unit disk graph embedding, thus cannot be present in a legal connectivity

graph.

Inside a fixed region, one cannot pack too many nodes without having edges in between. The forbidden

substructures we look for are actually those that violate

this packing argument.

ALGORITHM:

1. Find the forbidden parameter Fk based on value of k

selected

2. Each node u determines its 2k-hop neighbor list, N2k (u), and executes the following steps for each non

neighboring node v in N2k (u):

i. Node u determines the set of common k-hop

neighbors with v from their k-hop neighbor lists. This is Ck (u, v) = Nk (u) ∩ Nk (v)

ii. Node u determines the maximal independent set

of the sub-graph on vertices Ck (u, v) by using a

greedy approach iii. If the maximal independent set size is equal or

larger than fk , node u declares the presence of a

wormhole.

SYSTEM IMPLEMENTATION & TESTING

1) Setting Environment

To implement the proposed smoothly, we need to

have one of the various versions of LINUX operating

system which can be either Red Hat or Fedora or Ubuntu and we need to install the Network Simulator 2 version

2.2 or onwards software tool to support complete

functionality of the product.

In addition to NS-2, we developed a set of tools, mainly Bash scripts and AWK filters, to post-process the output

trace files generated by the simulator. Some scripts were

also written to help with the configuration and running of

the multiple experiments we have carried out. In order to evaluate the performance, we set up multiple

experiments. In every experiment, we run a NS-2

simulation for each type of attack and different scenarios.

The exact environment and parameters will be discussed.

System Execution Details

The system executes by simulating different attacks

individually and the tracing the values generated from these simulations.

Fig 3: The network simulation created for the DDoS attack

The first screenshot shows the simulation of the network

for the with total 16 nodes distributed in the diferent

groups. The nodes 4 and 9 are the nodes which takes the data coming from different distributed nodes for the other

part of the network.


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Fig.4: Service denied at node 16 due to dropping of legitimate packets

Fig. 4 shows the actual DDoS attack scenario where the

actual legitimate packets are dropped at node 15 and are

not sent to the destination node due the congestion in the

link and queue overflow .some of the packet may be sent

further to the actual destinations.

Fig 5: The graph showing the total number of packets

received

Fig. 5 shows the total no of packet received by the

destination node. From the graph it is clear that initially the received packet number is zero but when the attacker

nodes starts attacking the number of packets starts

increasing and after some time it continues to the

maximum capacity.

Fig.6: The graph showing the entropy of node 4

Fig 6 shows the entropy of node 4 In this the red line

indicate the ratio of the normal packets received to the

total packets received at node and the green line indicates the ratio of the attack packets received to the total packets

received at a node.

After the DDoS attack scenario the Wormhole attack is

simulated with the different environment.

Fig 7: simulation of Wormhole Attack

Fig 7 shows the simulation of the wormhole attack. Here

the unit disk graph method is used to detect the forbidden

nodes.

Fig. 8: Result of wormhole attack detection

After this the Blackhole attack is simulated.

Fig. 9 simulation of Blackhole Attack

RESULT ANALYSIS

After the simulation of the attacks the trace files generated

after the simulation of each of the attack is considered and

the values of different parameters are calculated as follows:

The different parameter values obtained for the Blackhole

attack in attack condition can be given in the table 4.1 as follows:


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Table 3. Results obtained for Blackhole attack

Parameter Value

Average energy 0.001246

Average end to end delay 0.418301

PDR 0.040323

The different values obtained for throughput can be given

as

Table 4. Throughput of blackhole attack at different conditions.

Throughput

Before attack During Attack

89.96538 7.3096

The different parameter values obtained for the DDoS

attack can be given in the table 4.3 as follows:

Table 5. Results obtained for DDoS attack

Parameter Value

Average Energy 0.0055

Average packet sent 14.8425

The different parameter values obtained for the Wormhole attack can be given in the table 4.4 as follows:

Table 6. Results obtained for Wormhole attack

Parameter Value

Average 2.63

End to end delay 0.014

The values of the packet delay for each of the attacks can be given as follows:

Table 7. Comparison table for the packet delay of the

network

Packet delay attcker DDoS Blackhole Wormhole

2 0.4138 0.4132 0.10056

3 0.42533 0.4192 0.12833

4 0.43133 0.4212 0.28

The comparative graph can be given between the three

attacks for the above table as below:

Fig 10.Comparative graph for packet delay in each of the attack

From the above results it is clear that the throughput of the

network decreases when the attack occurs. Also the attack

decreases the throughput to a large extent. The average

delay and the Packet delivery ratio also decreases when

there is an attack in the system.

CONCLUSION

From these discussions we can say that even if there are so many techniques for detection and prevention of different

types of attacks, no methodology provides the complete

protection from the attacks and also the each of these methodologies has some or other type of loophole in it.

Thus the system can detect and analyze the different

attacks and then provides a comparative study of these

attacks which proves that the wormhole attack provide less delay as compared to other two attacks, as the

detection technique used in the system restrict the attacker

nodes to disrupt the normal working of the system. This

system can provide a overview of the different types of attacks that can occur in the ad hoc networks

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