International Journal of Engineering Trends and Technology (IJETT) – Volume X Issue Y- Month 2015

ISSN: 2231-5381 http://www.ijettjournal.org Page 1

Malicious Node detection in Vehicle to

Vehicle Communication J.Nethravathy#1, Dr.G. Maragatham*2

#¹M.Tech Information Technology Student, #²Asst.Professor

SRM University, Kattankulathur, Kancheepuram District, India, Chennai 603 203 1nethramalathy@gmail.com

2 maragatham.g@ktr.srmuniv.ac.in

Abstract In vehicular communications, specifically

Vehicular Ad Hoc Networks (VANETs), is playing a

vital role in the future safety and ease of our roads.

VANETs will enhance driver safety and reduce

traffic deaths and injuries by implementing collision

avoidance and warning systems. In vehicular

networks, broadcast communications are critically

important, as many safety-related applications rely

on single-hop beacon messages broadcast to

neighbour vehicles. However, it becomes a

challenging problem to design a broadcast

authentication scheme for secure vehicle-to-vehicle

communications. Especially when a large number of

beacons arrive in a short time, vehicles are

vulnerable to computation-based Denial of Service

(DoS) attacks that excessive signature verification

exhausts their computational resources. In the

proposed system prediction based authentication

(PBA)[1] is used in the sender side to detect DoS

(Denial-of-Service)attacks before the signature

verification. And, the Enhanced attacked packet

detection algorithm [9] is used at the receiver side

to detect malicious node. To further reduce the

verification delay for some emergency applications,

PBA is designed to exploit the sender vehicle’s

ability to predict future beacons in advance. In

addition, to prevent memory-based DoS attacks,

PBA only stores shortened re-keyed Message

Authentication Codes (MACs) of signatures without

decreasing security. The simulation result

demonstrates that PBA fast verifies almost 99%

messages with low storage cost not only in high-

density traffic environments and also the secured

stateless protocol gives a better performance in

comparison to energy consumption and throughput

of network.

Keywords – Denial-of-service (DoS),Message

authentication codes(MACs), Prediction based

authentication(PBA),Enhanced Attacked packet

detection(EAPD).

I. INTRODUCTION

Vehicular ad hoc networks (VANETs) have recently

attracted extensive attentions as a promising

approach to enhance road safety, as well as to

improve driving experience. By using a Dedicated

Short-Range Communications (DSRC) technique,

vehicles equipped with wireless On-Board Units

(OBUs) can communicate with other vehicles and

fixed infrastructure, e.g., Road-Side Units (RSUs),

located at critical points of the road. Therefore,

Vehicle-to-Vehicle (V2V) and Vehicle-to-

Infrastructure (V2I) communications are regarded as

two basic types of communications in VANETs.

Once VANETs become available, numerous safe,

commercial and convenient services can be deployed

through a variety of vehicular applications. These

applications mostly rely on vehicles’ OBUs to

broadcast outgoing beacon messages and to validate

incoming ones. The broadcast beacons often contain

information about position, current time, speed,

direction, driving status, etc. For example, by

frequently broadcasting and receiving beacons,

drivers are better aware of obstacles and collision

scenarios. They may act early to avoid any possible

damage, or to assign a new route in case of a traffic

accident in the existing route.

II. SYSTEM DESIGN

A. Existing System:

In the existing system a one-time signature scheme

named Fast Auth [1] is used to provide lightweight,

timely and nonrepudiation authentication for

vehicle-to-vehicle communications. In Fast Auth

[1],the author have used chained Huffman hash trees

to generate a common public key and minimize the

signature size for beacons sent during one prediction

interval. Hence, Fast Auth first exploits the

predictability of future beacons to achieve the instant

authentication in VANETs.

Short comings:

If the receiver misses a beacon, it

cannot work in the rest of the current

prediction interval.

It cannot accurately collect the entire

beacon message

Also, it cannot increase the packet

delivery ratio.

International Journal of Engineering Trends and Technology (IJETT) – Volume X Issue Y- Month 2015

ISSN: 2231-5381 http://www.ijettjournal.org Page 2

B. Proposed system modules

The following are the details in the sender side and

receiver side details involved in the communication.

Sender

chained keys generation

position prediction

Merkle hash tree construction

signature generation

Receiver

Attack packet detection algorithm

Signature Verification

1) Sender Side Process:

Chained Key generation:

At the beginning of a time frame, each vehicle

generates n chained private keys for the next n

beacons. It uses one interval worth of private key for

authentications in TESLA scheme. In the following

description, we call these private key as TESLA

keys.

Position Prediction:

At each beacon interval, each vehicle predicts its

position broadcast in the next beacon. To do so,

vehicles model all the possible results of movements

between two consecutive beacons based on

information of the past trajectory.

Where [1]

(ai-ai-1,bi – bi-1)implies Pair of integers , prediction

table-PTi, collects all the possible message as - Mi.

Merkle hash tree construction (MHT):

Given the prediction table, the vehicle needs to

generate a single public key (or prediction outcome)

for all the possible movements. It first generates

private keys, which are associated with the results of

movements in PTi. Then, a MHT structure is

proposed to tie these keys together and generates a

single public key or prediction outcome for all the

movements. A MHT structure is a binary tree

structure where each leaf is assigned a hash value

and an inner node is assigned the hash value of its

children. The entry Mk in PTi shows that the vehicle

moves to the location [1] with a

certain probability in the interval Ii, there is a leaf

labelled as [1] in the

MHT, where Rik is a random value to prevent

signature forgery. The inner node is the hash of the

two children. The root of the MHT is also computed

by hashing the concatenation of its two children.

Then, the sender obtains Root1, which is the

predication outcome of the message Mi based on the

prediction table PTi.

PTi- prediction Table, Rik - random value, Ii-Interval, Mk-max message key

Signature Generation

After generating the commitment K0, constructing

the prediction table with a local coordinate, and

producing the MHT’s root Root1 for the next beacon

B1, the sender broadcasts the first beacon in a time

frame. It contains public keys, time stamp T0, and

other important parameters (such as, its local

coordinate system).Hence the first beacon is treated

as [1] where

[1] is

signed by ECDSA, and a Cert is issued by a CA.

K0-key, T0-Time stamp, P0-position.

2) Receiver side process:

Attack packet detection:

It is based on the position changing requirements.

Attacked packets are identified by the following

parameters Frequency (f), Velocity (v), Į is

Coefficient which is determined by the road

characteristics and (VMax) is the maximum speed,

f = Į * | v – VMax / 2|.. [9]

Frequency (F) is the numbers of broadcast

packets per Second, at attacked packets are

identified by the following Conditions. F and V are

high because the position will change quickly. F and

V are low because the vehicle positions will not

change much. It is based on the change in the

Position and change frequency f, velocity v.

Signature Verification:

For the first beacon B0, ECDSA signature can

provide the property of non-repudiation. It helps the

receiver ensure that the sender is accountable for the

parameters such as the initial position ~ P0 and the

commitment of hash chains K0, and thus prevents

drivers from broadcasting malicious information. To

verify the following signed Bi, the receiver verifies

the validity of Ki-1 by following the one-way

keychain back to K0 signed with ECDSA. It

recomputes the root value Rooti’ of MHT given

relevant values in the mi, and checks whether it

matches Rooti stored in the memory. If not, the

receiver will verify mi with the later TESLA key.

International Journal of Engineering Trends and Technology (IJETT) – Volume X Issue Y- Month 2015

ISSN: 2231-5381 http://www.ijettjournal.org Page 3

III. SYSTEM OVERVIEW

The RSU plays a vital role in identifying the

malicious node packets and clears those packets with

correct packets with respect to all the vehicles in the

scenario.

Fig.1 The Presence of RSU, malicious node

and other vehicles in the Highway.

IV. System Flow:

International Journal of Engineering Trends and Technology (IJETT) – Volume X Issue Y- Month 2015

ISSN: 2231-5381 http://www.ijettjournal.org Page 4

V. IMPLEMENTATION RESULT

In the existing system – PBA approach, the factors

such as Security issues, end to end delay aspects and

packet delivery time are accounted and the proposed

approach has shown improved results which were

encouraging. The experiment is carried out using

NS2, fedora 8 with Hard Disk 40GB, Processor

above 500MHZ, RAM 512MB .Following are the

simple screen shots of the proposed work.

Fig.2 Vanet communication

Fig.3 Chained key and position production

Fig.4 Vanet communication sending information

Fig.5 Malicious node find

Fig.6 Malicious node detected

Fig. 7 End to end delay

International Journal of Engineering Trends and Technology (IJETT) – Volume X Issue Y- Month 2015

ISSN: 2231-5381 http://www.ijettjournal.org Page 5

Fig.8 Packet delivery and reliability

VI. CONCLUSION

The enhanced Prediction-based Authentication

protocol is secure and robust in the context of

VANETs. The EAPDA algorithm [9] is used to

improve the security of VANET system and to avoid

the delay overhead in early time. The proposed

algorithm which integrates PBA [1] and EAPDA [9]

helps to achieve the high packet delivery ratio and

minimizes the delay overhead.

Future Work:

As, the above method identifies malicious packets

sent by a single node. Enhancement can be made by

improved methods to detect multiple malicious

packets received by a node.

REFERENCES

[1] PBA: Prediction-based Authentication for Vehicle-to-

Vehicle Communications Chen Lyu, Dawu Gu, Yunze Zeng, Prasant Mohapatra

[2] International Journal of Computer Applications (0975

– 8887) National Conference on Recent Trends in Computer Applications NCRTCA 2013 “A Cluster-based

Highway Vehicle Communication in VANET”

[2] Halabi Hasbullah, Irshad Ahmed Soomro, Jamalul-lail Ab Manan, “Denial of Service (DOS) Attack and Its Possible

Solutions in VANET” in International Scholarly and

Scientific Research & Innovation 2010. [3] Aditya Sinha & Santosh K. Mishra, “Queue

LimitingAlgorithm (QLA) for Protecting VANET from

Denial of Service (DoS) Attack” published in International

Journal of Computer Applications (0975 – 8887) Volume

86 – No 8, January 2014.

[4] K. Shim, “Reconstruction of a secure authentication scheme for Vehicular ad hoc networks using a binary

authentication tree,” IEEE Transactions on Wireless

Communications, vol. 12, no. 11,pp. 5586-5393, Nov. 2013.

[5] Y. Hao, Y. Cheng, C. Zhou, and W. Song, “A distributed

key management framework with cooperative message authentication in vanets ,” IEEE Journal on Selected Areas

in Communications, vol. 29, no. 3, pp. 616-629, Mar. 2011.

[6] [8] International Journal of Advanced Research in Computer and Communication Engineering Vol. 4, Issue 6,

June 2015 “A Survey on VANET Security using ECC,RSA

& MD5” [7] Enhanced attacked packet detection algorithm for

Detecting attack in vanet1.priya Sharma2.Amarpreet sign

Proceedings of 38th IRF International Conference, 27th September 2015, Pune, India, ISBN: 978-93-85832-03-1

[8] Wireless LAN Medium Access Control (MAC) and Physical

Layer (PHY) Specification, IEEE Std. 802.11, 1997.