International Journal of Engineering Trends and Technology (IJETT) – Volume 33 Number 5- March 2016
International Journal of Engineering Trends and Technology (IJETT) – Volume X Issue Y- Month 2015
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 highdensity 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.
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-toInfrastructure (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.
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:

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
ISSN: 2231-5381
SYSTEM DESIGN

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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.
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B. Proposed system modules
The following are the details in the sender side and
receiver side details involved in the communication.
PTi- prediction Table, Rik - random value, IiInterval, Mk-max message key
Sender




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.
chained keys generation
position prediction
Merkle hash tree construction
signature generation
Signature Generation
Receiver
 Attack packet detection algorithm
 Signature Verification
1) Sender Side Process:
as
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
ISSN: 2231-5381
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
[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 ~ P 0 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.
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International
Journal
of of
Engineering
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and
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– Volume
33XNumber
March2015
2016
International
Journal
Engineering
Trends
and
Technology
(IJETT)
– Volume
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III.
SYSTEM OVERVIEW
IV.
System Flow:
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.
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International
Journal
of of
Engineering
Trends
and
Technology
(IJETT)
– Volume
33XNumber
March2015
2016
International
Journal
Engineering
Trends
and
Technology
(IJETT)
– Volume
Issue Y-5-Month
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.5 Malicious node find
Fig.2
Vanet communication
Fig.6 Malicious node detected
Fig.3 Chained key and position production
Fig. 7 End to end delay
Fig.4 Vanet communication sending information
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International
Journal
of Engineering
Trends
andand
Technology
(IJETT)
– Volume
33 X
Number
March2015
2016
International
Journal
of Engineering
Trends
Technology
(IJETT)
– Volume
Issue Y-5-Month
improved methods to detect multiple malicious
packets received by a node.
REFERENCES
[1]
[2]
[3]
Fig.8
Packet delivery and reliability
VI.
CONCLUSION
[4]
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
ISSN: 2231-5381
[5]
[6]
[7]
[8]
PBA: Prediction-based Authentication for Vehicle-toVehicle Communications Chen Lyu, Dawu Gu, Yunze
Zeng, Prasant Mohapatra
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Aditya Sinha & Santosh K. Mishra, “Queue
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86 – No 8, January 2014.
K. Shim, “Reconstruction of a secure authentication
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Enhanced attacked packet detection algorithm for
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Proceedings of 38th IRF International Conference, 27th
September 2015, Pune, India, ISBN: 978-93-85832-03-1
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