International Journal of Engineering Trends and Technology (IJETT) – Volume 35 Number 1- May 2016
A Survey on Reputation System and Price
System Based Cooperation Inducement Scheme
in Mobile Adhoc Networks
Manikandan.E#1, Muthukumarasamy.S#2, Thanigaivelu.K#3,
S.A. Engineering College, Chennai, India
Abstract -Mobile ad-hoc network is a decentralized
dynamic network .It is an infrastructure less network
of mobile nodes. So, sometimes mobile devices are
untrustworthy. If the mobile device wants to
communicate with other mobile device present out of
its communication range, it has to transmit the data
via multiple relay nodes. The relay nodes should
cooperate with the source node to forward the data
towards the destination. Due to the lack of resources,
some mobile devices may refuse to cooperate with the
source node. The cooperation inducement schemes
can extensively encourage the mobile devices to
assist other mobile devices to transmit the data to the
far away destination. The aspiration of this paper is
to review the delegated cooperation inducement
schemes used to encourage the mobile nodes to
actively participate in the other node’s
communication. The individual features are
examined and the limitations are conferred.
deviation may be unintentional (i.e) owing to fault in
hardware, link breakage due to mobility or may be
intentional (i.e) selfish or attacker to take the benefit
of convinced situation. The selfish nodes are not
relay the data packets of other nodes in order to save
its own resources but it expect other nodes to forward
its data packets. The attacker or malicious node
disturbs the regular function of the network.
Keywords- mobile ad-hoc, node, data.
The Cooperative inducement schemes are
generally classified into two. They are,
The cooperation inducement schemes are
feasible to recover the above stated problem in
MANET communication. It provides the lightweight
solution instead of using cryptographic techniques
involves signature schemes and certificate exchange.
The cryptographic schemes consume much resource
and create overhead in the communication. The
cooperation inducement schemes create the soft layer
in MANET to guard the regular operations of
MANET.
I. INTRODUCTION
The Mobile Adhoc Network is a network of
independent mobile devices linked via wireless link
devoid of any communication infrastructure. The
MANET is a dynamic network which means that the
topology of the network changes dynamically. All the
mobile devices enter into or exit from the
communication range of other mobile device
dynamically. This will provoke the multihop
communication in MANET. At the same time, the
destination node is far away from the source node
will also provoke the multihop communication.
The efficiency or reliability of MANET
communication relies on cooperation among the
mobile devices. The misbehavior nodes decline to
cooperate with other nodes to save its resources. The
occurrence of uncooperative nodes in the path
towards the destination will seriously affect the
performance of the MANET communication. In this
context, misbehavior of nodes refers to divergence
from functionality of normal mobile device. This
ISSN: 2231-5381
Reputation system to set up trust level
Pricing and credit based schemes
Reputation system is used to create the reputation
value for each mobile devices based on the trust
level. Pricing and credit based schemes offers
monetary inducements to encourage the mobile
devices for active cooperation with other nodes. In
this paper, we have analyzed various delegated
cooperation inducement schemes proposed in related
research articles. The merits and demerits of those
schemes are analyzed in this paper.
The rest of the paper is ordered as follows: - Section
II review reputation schemes, Audit based schemes
and credit based schemes. Section III thrash out our
findings and section IV concludes this article.
II. REPUTATION SCHEMES
This section reviews five representative reputation
schemes and discusses their unique characteristics.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 35 Number 1- May 2016
A. CONFIDENT
B. CORE
It is a reactive routing protocol for dynamic network
which follows the features of Dynamic Source
Routing (DSR). In this secure routing protocol, if the
misbehaving nodes are detected, normal nodes are
not forward the data packets coming from the
misbehaving nodes. The misbehaving nodes are
removed from the route cache and cannot participate
in the routing decision. The mobile devices those are
using CONFIDENT protocol have following four
mechanisms:
In [2], the authors distinguish the selfish nodes from
the malicious nodes. The selfish node use their
resources for their own communication alone while
not cooperate with other nodes in packet forwarding
towards the destination. The selfish nodes expect
other nodes to cooperate with them. The malicious
nodes affect its neighbor nodes by making network
unavailable. The authors proposed a novel technique
Collaborative Reputation mechanism (CORE) to
insist the cooperation among the mobile nodes in
MANET. Three types of reputation values are used
by the CORE such as,
Monitor
Reputation system
Path Manager
Trust Manager
Indirect Reputation
Subjective Reputation
Functional Reputation
The monitor component in the mobile device enables
mobile nodes to examine the nearby nodes for any
divergences in the source route by continuously
monitor the transmission of the nearby node or by
scrutinize the routing protocol performance. If the
node detects any misbehavior among the neighbor
node, it will distribute the warning information by
transmitting ALARM message (Evidence) to the trust
manager component. The trust manager component
evaluates the source of the data packets. A node
confirms a particular node is a misbehaving node
based on the number of acceptable ALARM
messages it receives is called as rating. A node will
analyze the ALARM message based on sufficient
proof of malicious misbehavior of nodes. When the
rating exceeds the certain threshold level, that node is
confirmed as the malicious node.
A node determines the evidence value from
its own monitoring system and from Trust manager
in the form of ALARM messages. The evidence
value from the Trust manager get less significance
than the evidence value from its own monitoring
system. Each mobile node upholds the Local rating
list or black list and exchanges these lists with the
normal nodes in its communication range. In the
route discovery process, a node sends the route
request to the nodes which are not in the black list.
This will shun the presence of malicious nodes in the
route to reach the destination. The black list is also
used to neglect the request from the malicious node.
So, the nodes do not forward the packets for the
nodes with bad rating.
Subjective Reputation is the reputation value
determined based on the local observation of a node
with respect to other mobiles nodes in the network.
Indirect reputation is the reputation value get from
other nodes in the network. Functional reputation is
computed by merging the subjective reputation and
the indirect reputation by using weighted combining
formula to obtain the final reputation value in order
to select a node to forward the packet. The functional
reputation values are combined together to determine
the global reputation value. Subjective reputation
values get updated with respect to the misbehavior
identification by watchdog mechanism. Indirect
reputation values get updated with respect to the
reply message. The reply message contains the
information about the truthful behavior identified in
each operation. If the reputation of a mobile node is
negative, the request from that mobile node is denied
by all other remaining nodes in the network. The
CORE failed to consider the second chance method.
C. OCEAN
OCEAN stands for Observation based Cooperation
Enforcement in Ad hoc Networks. This mechanism
prohibits whichever second hand information
exchanges to reduce the selfishness in adhoc
networks. In this technique, a mobile select the path
to reach the destination based on the information get
by examining its neighbor nodes available inside its
communication range honestly. OCEAN [3] follows
the route discovery process of DSR routing protocol.
This protocol consists of five modules. They are,
Neighbor Watch
Route ranker
Rank based routing
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International Journal of Engineering Trends and Technology (IJETT) – Volume 35 Number 1- May 2016
In Neighbor watch module, each mobile node
monitors the behavior of its neighbor nodes. Based
on that, a mobile node calculates the rate for each
neighbor nodes and maintains the rating for each
mobile node in the Route ranker module. The next
forwarder node is selected based on the rating given
to the neighbor nodes. Mobile nodes forward its data
to its neighbor node with highest rank. This type of
routing is called Rank based routing. This will avoid
the participation of malicious nodes in the route.
OCEAN uses the second chance mechanism to
remove a normal node from the malicious list.
Whenever the rating of the neighbor nodes is lesser
than the threshold value, it will be added into the
malicious list. The prohibition of second hand
information avoids reduces the selfishness behavior
of mobile nodes. The OCEAN protocol is more
durable to rumor spreading because it uses only first
hand information for routing decision.
D. LARS
In [4], the authors have proposed locally aware
reputation system to encourage the cooperation
among the mobile nodes. LAR also prevents the
participation of misbehaving nodes in the
communication. Each node estimates the reputation
value of its neighbor nodes. The reputation value is
calculated only based on the direct observation of the
behavior of its neighbor nodes. In LAR, the evaluator
node discovers the misbehaving nodes in the network
based on the reputation value. If the reputation value
falls below the threshold, the evaluator node notifies
that node by transmitting WARNING message. If the
WARNING message issued by the evaluator node is
cosigned by other neighbor nodes, that node is
considered as malicious node. This will prevent the
false identification of misbehaving nodes. In LAR,
the misbehaving nodes are not removed from the
network. After some time period, it will be accepted
but the reputation value is unchanged.
Reputation Management
Trust worthy Route discovery
Identification of misbehaving nodes
AMD assesses the performance of a node in a Perpacket basis. AMD does not use the energy exclusive
overhearing techniques or rigorous acknowledgement
schemes. It will reduce the selfishness behavior of
nodes in the network. AMD can avoid the
misbehaving nodes in the communication even
maximum number of nodes become selfish nodes.
F. REAct
REAct [6] explores the crisis of recognizing the
misbehaving nodes that decline to forward the
packets. It provides resource proficient liability for
node misbehavior. The slump in the performance of a
node is audited randomly to get the series of random
audits. Based on this information only, REAct
discovers the mischievous node in the network.
Additionally, REAct uses the behavioral proofs to
identify the misbehaving nodes. These behavioral
proofs are built by using Bloom filters. So, REAct
diminishes the communication overhead to detect the
misbehaving nodes in the network.
G. Credit Based Systems
Credit based systems is mainly used to offer the
incentive to the nodes for forwarding other node’s
packets. In [7], the authors have proposed a
architecture, in which each node get the credit for
each packet they forward and use that credit when it
need to transmit its own packets. In [8], the authors
have proposed a new credit based system called
Sprite. Sprite gathers receipts for each packet it
forwards to other nodes. Each node uploads the
receipts in Credit Clearance Service (CCS) and gets
the credits. The credit based systems inspire the
selfish nodes to cooperate in the communication but
they provide no incentive to misbehaving nodes.
III. AUDIT BASED SYSTEMS
IV. CONCLUSION
Audit based Systems effectively identify and
segregate the misbehaving nodes those are disagree
to forward the data packets of other nodes from the
network. In this section, we discuss about two audit
based mechanism.
E. AMD
Audit based misbehavior detection (AMD) segregate
[5] the black hole and grayhole attackers. Black hole
attacker continuously drops the data packet mean
while grayhole attacker selectively drops the data
packet. AMD consist of following modules:
ISSN: 2231-5381
This paper surveyed various delegated cooperation
inducement schemes and the distinctive features of
those schemes are discussed. The advantages and
disadvantages of those schemes are noticed. The
reputation based schemes; the pricing and credit
based schemes individually provide the solution to
the problem of uncooperation among the mobile
nodes but they are leads to expenditure resource
consumption and cannot provide the adequate
solution for cooperation inducement.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 35 Number 1- May 2016
Wireless Sensor Networks, Wireless Networks,
Information Security.
REFERENCES
[1]Buchegger, S. Le Boudec J.-Y.,, 2002. “Performance analysis of
the confidant protocol (cooperation of nodes: fairness in dynamic
ad hoc networks)”, in MobiHoc’02, IEEE/ACM Symposium on
Mobile AdHoc Networking and Computing.
[2]Michiardi, P., Molva, R., 2002. “Core: a collaborative
reputation mechanism to enforce node cooperation in mobile adhoc networks”, in CMS’02, Communications and Multimedia
Security Conference.
[3]Bansal, S., Baker, M., 2003. “Observation-based Cooperation
Enforcement in Ad hoc Networks”, arxiv:cs/0307012v2.
[4]Hu, J., Burmester, M., 2006. “LARS: a locally aware reputation
system for mobile ad-hoc networks”, in 44th annual ACM
Southeast Regional Conference.
THANIGAIVELU.K#3 is a Professor
in
Department
of
ECE
at
S.A.Engineering
College.
He
completed his PhD in Information
Communication and Engineering at
Anna University and completed M.Tech in Laser &
Optical Engineering in 1999 at Anna University and
B,.tech in Electronics in 1995 at Madras University.
His areas of interests include Antennas, Wireless
Sensor Networks, Network Security, Grid Computing
[5]Yu Zhang, Loukas Lazos, William Kozma, "AMD: Audit-based
Misbehavior Detection in Wireless Ad Hoc Networks," IEEE
Transactions on Mobile Computing, 06 Sept. 2013.
[6]William Kozma Jr., Loukas Lazos. “REAct: Resource-Efficient
Accountability for Node Misbehavior in Ad Hoc Networks based
on Random Audits”, 10th IEEE Symposium on Computers and
Communications, 27-30 June 2005.
[7]L. Buttyan and J.-P. Hubaux, “Stimulating Cooperation in Selforganizing Mobile Ad hoc
Networks”, Mobile Net. and
Applications, 8(5):579–592, 2003.
[8]S. Soltanali, S. Pirahesh, S. Niksefat, and M. Sabaei, “An
Efficient Scheme to Motivate Cooperation in Mobile Ad hoc
Networks”, In Proc. of ICNS, pages 92–98, 2007.
MANIKANDAN.E#1 is a PG Scholar
in Department of Computer Science
and Engineering at S.A.Engineering
College. He received his B.E. in
Computer and Engineering from
Maamallan Institute of Technology, Sriperumbudur
in 2014. His area of interests includes Mobile
Computing, Wireless Sensor Networks, Wireless
Networks, Wireless Communication.
MUTHUKUMARASAMY.S#2 is
pursuing his (Ph.D.) in Department
of
Computer
Science
and
Engineering at Anna University. He
received his B.E. in Computer and
Engineering from E.G.S.Pillay Engineering College,
Nagapattinam in 2005 and M.E. in Computer Science
and Engineering from Sri Krishna Engineering
College, Chennai in 2011 . He is currently working as
Assistant Professor in S.A.Engineering College. His
area of interests includes Mobile Computing,
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