TRUST MANAGEMENT FOR DELAY TOLERANT NETWORK

http://www.iaeme.com/IJCIET/index.
International Journal of Civil Engineering and Technology (IJCIET)
Volume 8, Issue 2, February 2017, pp.
Available online at http://www.iaeme.com/IJCIET/issues.
ISSN Print: 0976-6308 and ISSN Online: 0976
© IAEME Publication Scopus
TRUST MANAGEMENT FOR
Reasearch Shcholar, Bharath University, Chennai,
Professor, Sri Ramanujar College of Engineering, Chennai
ABSTRACT
Delay Tolerant Networks (DTNs) have high end
disconnection, and unreliable wireless connections. It does not mean a delay service instead
DTNs provides a service where network imposes disruption or delay. It operates in
networks with extremely limited resources such as memory size, CPU processing power etc.
This paper presents an efficient trust managing mechanism for providing secure environment.
The proposed dynamic trust management protocol uses a dynamic t
overcomes the problems with time changing dynamic characteristics by dynamically updating
the criteria in response to changing network conditions. This reduces overheads and increases
the efficient use of routing network even in con
update reduces the false detection probability of the malicious nodes. To show the effectiveness
of the proposed system, a detailed simulation in the presence of selfish and malicious nodes is
performed with ONE simulator. Finally a comparative analysis of our proposed routing with
previous routing protocols is also performed. The results demonstrate that presented algorithm
deals effectively with selfish behavior with providing significant gain on effective delive
in trade off with message overhead and delay.
Key words: Almatti, Netflows, CWC gauge data,
Cite this Article: C. Rukkumani and Dr. Krishna Mohanta
Tolerant Network. International Journal of Civil Engineering and Technology
08–12.
http://www.iaeme.com/IJCIET/issues.
1. INTRODUCTION
Wireless Delay Tolerant Network (DTNs) [1] is a new Networks class which is characteriz
long message delay and lack of a fully connected path between the source and the target nodes. As a
result, the use of mobile nodes acting as a buffer between the one to other end and behave as a store
and forward approach. The message moves to a n
messages reach their destinations. The message sending is an opportunistic procedure because the
messages are sent in an opportunistic way. Because of its characteristics wide range of useful
applications have been developed for DTNs and enable a new class of networking applications in the
wireless network interface which increases popularity of mobile devices. DTNs can be used for
IJCIET/index.asp 8
International Journal of Civil Engineering and Technology (IJCIET)
2017, pp. 08–12 Article ID: IJCIET_08_02_002
http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=8&IType=2
6308 and ISSN Online: 0976-6316
Scopus Indexed
TRUST MANAGEMENT FOR DELAY TOLERANT
NETWORK
C. Rukkumani
Reasearch Shcholar, Bharath University, Chennai, India
Dr. Krishna Mohanta
Professor, Sri Ramanujar College of Engineering, Chennai, India
Delay Tolerant Networks (DTNs) have high end-to-end latency, which is often faces
DTNs provides a service where network imposes disruption or delay. It operates in
The proposed dynamic trust management protocol uses a dynamic threshold updating which
the efficient use of routing network even in conditions change. Also the dynamic threshold
imulator. Finally a comparative analysis of our proposed routing with
deals effectively with selfish behavior with providing significant gain on effective delive
in trade off with message overhead and delay.
atti, Netflows, CWC gauge data, working tables, Catchment
C. Rukkumani and Dr. Krishna Mohanta, Trust Management for Delay
International Journal of Civil Engineering and Technology
http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=8&IType=2
Wireless Delay Tolerant Network (DTNs) [1] is a new Networks class which is characteriz
and forward approach. The message moves to a new node when it appears in the range, similarly the
have been developed for DTNs and enable a new class of networking applications in the
editor@iaeme.com
asp?JType=IJCIET&VType=8&IType=2
DELAY TOLERANT
India
, India
end latency, which is often faces
DTNs provides a service where network imposes disruption or delay. It operates in challenged
hreshold updating which
ditions change. Also the dynamic threshold
imulator. Finally a comparative analysis of our proposed routing with
deals effectively with selfish behavior with providing significant gain on effective delivery ratio
working tables, Catchment
Trust Management for Delay
International Journal of Civil Engineering and Technology, 8(2), 2017, pp.
asp?JType=IJCIET&VType=8&IType=2
Wireless Delay Tolerant Network (DTNs) [1] is a new Networks class which is characterized by a
ew node when it appears in the range, similarly the
have been developed for DTNs and enable a new class of networking applications in the

C. Rukkumani and Dr. Krishna Mohanta
http://www.iaeme.com/IJCIET/index.asp 9 editor@iaeme.com
developing low-cost internet services on remote area moreover it can be used for vehicle DTNs for
local advertising, location-based information collection such as traffic reports and parking
information. However, the practical DTNs implementation is questionable because its characteristics
making them vulnerable to serious security threats. In the system every node predicted that
intermediate nodes (or vehicles) are relaying the message properly. However malicious node not
carries the message properly in the network which causes multi-hop communications to fail and
detection of their presence may be hard. DTNs relay carriers sharing which is the essential
requirement, but this cannot be guarantee because selfish nodes can avoid participating for other
messages. On other hand malicious node creates the black hole which carries out attacks by
deliberately dropping messages. Overcome these attacks is a real challenge due to the connectivity and
distributed nature of DTNs. DTN are resource constrained in nature to save its own resources and
nodes may develop selfish behavior. In which its drop the packet of other nodes to maximize its own
credit or benefits. Such nodes increase the message drop probability and reduce the message delivery
rate. In this paper, we propose a dynamic trust based approach to protect network from black hole and
selfish attacks. The rest of the paper is organized as follows: the second section provides a brief
discussion of the most recent relative literatures of DTNs and the system model is defined in third
section. The fourth section explains the proposed algorithm and the simulated results and the fifth
section explain about conclusion and future work on the basis of the simulation results presented in
fourth section.
2. LITERATURE REVIEW
Since the security in the DTN has already an open issue hence this section presents a brief review of
some of the recent and relevant literatures. E. Bulut [2] presented a study on DTNs in presence of
malicious nodes (also known as compromised DTNs). The literature analyzes the effects of malicious
nodes presence on routing in compromised DTNs. They also proposed a two period routing to
achieving the required delivery ratio with limited packet lifetime in presence of malicious nodes. The
variants of social psychology based approach is one of the commonly found and widely applied [3] [4]
[11] [12] because of their similarity with structure of the DTNs. These methods works by checking
social characteristics like locality, community and relations to decide packet forwarding or consider
other characteristics such as selfishness, unwillingness to avoid packet forwarding. Most of the
literature shows that these techniques can effectively improve the routing performance of DTN. A
combined social psychology and game theory is presented in [3] [8] which utilize the game theory to
find the solution and cause of the social misbehaving. A probabilistic technique for nodes misbehavior
detection and efficient trust establishment named iTrust is proposed by Haojin Zhu [8]. The iTrust
utilizes the Trust Authority (TA) to periodically check the nodes behavior by cost. Trust Authority is
small in numbers because it is fixed and little bit costly, so availability of TA probability cannot be
guaranteed if network size is large. Another common approach [11] is trust management which works
by estimating the trust level of the nodes either by locally orglobally. Generally the trust is estimated
by observing the packets in surrounding environment. Since the trust estimated by any node is shows
its own criteria or vision and the major problem with such systems are false negative trust estimation
because of nodes visibility, hence effective approaches are required to reduce the false detection.
Geographic routing protocol is one of the recent approaches but they required special costly hardware
such as GPS, directional antennas etc. Ing-Ray Chen [9] proposed and analyzes the trust management
protocols for encounter based routing. They incorporated in quality-of-service (QoS) trust properties
(connectivity) and social trust based properties (honesty and unselfishness) for trust evaluation in the
routing protocol. In their literature review two different protocols, an equal-weight QoS, social trust
based management protocol and a QoS only trust management protocol are considered. A Credit
Based Incentive System is proposed in [5], which allows the routing protocol to search the most
efficient routes, with incentive considerations, hence protect against behavior of purposely waste
transfer opportunity and unfairly increased rewards of selfish nodes. The algorithm also provides

Trust Management for Delay Tolerant Network
different incentive mechanisms to effectively handle different properties. A secure data forwarding
scheme is presented by Mohamed Elsalih Mahmoud [6], they named it SATS. The SATS uses credits
to measure the node’s cooperation in forwarding other node’s messages and to maintain fairness. It
also utilizes a trust system to assign a specific trust value to each node. A node’s trust value indicates
that how actively it forwards other’s messages. The nodes with high trust values are preferable in data
forwarding to avoid the attackers that are not participating in routing process. The SATS forces nodes
for cooperation to only earn trust but also maintain it at higher values. Haojin Zhu [7] proposed a
multilayer credit based incentive technique, to encourage forwarding cooperation among DTN nodes.
The scheme has feature to operate in a fully distributed manner to defend various attacks without
depending upon any specialized hardware. The performance of proposed method is further increased
by different optimization techniques by exploiting the unique characteristics of DTNs.
3. SYSTEM MODEL
In the present work we consider the DTN environment without any centralized trusted authority (TA).
Nodes are able to use multi hops communication. Node exchanges the information on encounters with
another node.
3.1. System Behavior and Model
The system behavior of the node is defined as the unwillingness of node in participation of its
resources on others requirement, this is generally done to maintain its limited resources such as power.
Since DTNs required participation of all nodes in packet relaying this could cause severe degradation
of the performance. They considered selfish nodes acts for its own interests, so to save energy it just
drop the packet but it may decide to forward a message with a certain probability. Two kind of
selfishness: 1. Individual Selfishness: Here node forwards only those packets which are generated by it
and drop packets from other node. 2. Social Selfishness: Here nodes are willing to forward packets for
other nodes with whom they have social connect but not others and such willingness varies with the
strength.Strategies [13] for prevention of selfishness are as follows: 1. Barter Based 2. Credit Based 3.
Reputation Based Barter Based is pair wise Tit-For-Tat strategy. The procedure is that two encounter
nodes exchange the equal value of messages. A message in which the nodes are interested is called
primary message and other are secondary messages, hence it degrades the performance of nodes
drastically.
Credit Based strategy are cooperative to forward the messages, the idea is to gets certain amount of
credit as a reward that it can later explore for its own profit. Credit Based are generally of two types:
Message Purse Model and Message Trade Model. In Message Purse Model source node pay credits to
the intermediate nodes which are involve in forward the messages to the destination. In Message Trade
Model the sender of the message pay credits to receivers in each hop-by-hop transmission until the
message reach the destination, which finally pays credits for the message forwarding. Reputation
Based strategy based upon cooperative experiences and observation of its past activities. If the
reputation value of a node is less, it reflects that the node is selfish according to other nodes, otherwise
Cooperative nature to the nodes. Each intermediate node receives a reputation value after pass a
message to other nodes. The reputation value is a proof about the cooperative nature of the
intermediate node. Reputation Based are generally of two types: Detection Based Model and Without
Detection Based Model. In Detection Based every node detects the behaviour of the receiver which
receives the message from him, in order to monitor the selfishness and encourage them to be
cooperative in nature. In reputation the node is punished if it is not cooperate in nature. Reputation is
also used in Social Selfishness Aware Routing (SSAR), the performance of the node is not affected by
the not well-behaved nodes. First check the willingness of receiving node if it is ready then the
message with higher delivery probability in the network is transferred.When a node behave as a selfish
then forward the messages only to its community while a malicious node aims to break all the

C. Rukkumani and Dr. Krishna Mohanta
protocols of basic DTN routing functionality. A malicious node drops the packets and also performs
the trust related attacks:
• Self-promoting attacks: To attract other packets in the network its increase own importance by
providing good credits or recommendations for itself.
• Bad-monitoring attacks: It decreases the probability of packet routing through good nodes by providing
bad recommendations and its ruin the reputation of well-behaved nodes.
• Ballot stuffing: It increase the probability of packet transfer through malicious node by proving good
recommendations to the bad nodes, it increase the reputation of not well-behaved nodes. A malicious
node attacker performs random attacks to evade detection. We introduce a new random attack
probability to reflect random attack behavior. When random attack probability is equal to 1, the
malicious attacker is a reckless attacker, when random attack probability is less than 1 it is a random
attacker. The node trust value is directly accessed by the trust evaluation and indirect trust value by
recommendations. Upon the encounter process the one node trust is depend upon other.
Trust protocol is independently run by each node. Most of the detection scheme [14] focuses on
the detection of node. However after detection how their behavior can change and how they can be
motivated to avoid such malicious behavior haven’t been explained anywhere. We have also focused
on the scenario when an honestly behaved node changes it’s behavior then how it’s should be
motivated to do honest behaviour.
4. CONCLUSION
In this paper, we first classified the selfish behavior in DTNs and then existing strategies for
preventing selfish behavior. We subsequently analyzed the mechanisms and explored techniques of
the proposed strategies. Further, we pointed out the problems in previous technique. The previous
strategy cannot work in an environment in which the node saves a high probability of being selfish to
other nodes. But, we conducted an experiment to investigate the performance of the representative
strategies in each category. The results of our experiment illustrate that the performance of proposed
strategies outperforms the previous technique.
REFERENCES
[1] "The ns-3 Network Simulator," Nov. 2011, http://www.nsnam.org/.
[2] E. Ayday, H. Lee, and F. Fekri, “Trust Management and Adversary Detection for Delay Tolerant
Networks,” in Military Communications Conference, 2010, pp. 1788-1793.
[3] E. Ayday, H. Lee, and F. Fekri, “An Iterative Algorithm for Trust Management and Adversary
Detection for Delay Tolerant Networks,” IEEE Transactions on Mobile Computing,
DOI:10.1109/TMC.2011.160, online avaiable, 2011.
[4] E. Bulut, Z. Wang, and B. Szymanski, “Cost Effective Multi-Period Spraying for Routing in Delay
Tolerant Networks,” IEEE/ACM Transactions on Networking, vol. 18, no. 5, 2010, pp. 1530-1543.
[5] E. Bulut, Z. Wang, and B. K. Szymanski, “Impact of Social Networks on Delay Tolerant Routing,”
in IEEE Global Telecommunications Conference, Honolulu, HI, Nov. 2009, pp. 1-6.
[6] J. Burgess, B. Gallagher, D. Jensen, and B. N. Levine, “Maxprop: Routing for Vehicle-Based
Disruption-Tolerant Networking,” in IEEE Conference on Computer Communications, Barcelona,
Spain, April 2006, pp. 1-11.
[7] V. Cerf, S. Burleigh, A. Hooke, L. Torgerson, R. Durst, K. Scott, K.Fall, and H. Weiss, "Delay-
Tolerant Networking Architecture," RFC 4838, IETF, 2007.
[8] M. Chang, I.-R. Chen, F. Bao, and J.-H. Cho, “Trust-Threshold Based Routing in Delay Tolerant
Networks,” in 5th IFIP International Conference on Trust Management, Copenhagen,Denmark,
June 2011, pp. 265-276.

Trust Management for Delay Tolerant Network
[9] I.-R. Chen, F. Bao, M. Chang, and J.-H. Cho, “Trust Management for Encounter-Based Routing in
Delay Tolerant Networks,” in IEEE Global Communications Conference, Miami, Florida, USA,
Dec.2010, pp. 1-6.
[10] E. M. Daly, and M. Haahr, “Social Network Analysis for Information Flow in Disconnected Delay-
Tolerant MANETs,” IEEE Transactions on Mobile Computing, vol. 8, no. 5, May 2009, pp.606-
621.
[11] G. Dini, and A. L. Duca, “A Reputation-Based Approach to Tolerate Misbehaving Carriers in
Delay Tolerant Networks,” in 15th IEEE Symposium on Computers and Communications,
Riccione, Italy,June 2010, pp. 772-777.
[12] F. Li, J. Wu, and A. Srinivasan, “Thwarting Blackhole Attacks in Disruption-Tolerant Networks
using Encounter Tickets,” in IEEE Conference on Computer Communications, 2009, pp. 2428-
2436.
[13] Priti Bhardwaj and Rahul Johari, Routing in Delay Tolerant Network Using Genetic Algorithm.
International Journal of Computer Engineering and Technology (IJCET), 4(2), 2013, pp. 590–597.
[14] M V Rathnamma and Dr. P. Chenna Reddy, Trust Management Scheme for AD-HOC Networks
Using a Social Network Based Approach for Secure Routing. International Journal of Computer
Engineering and Technology (IJCET), 4(3), 2013, pp. 359–369.

TRUST MANAGEMENT FOR DELAY TOLERANT NETWORK

More Related Content

What's hot (14)

Viewers also liked (20)

Similar to TRUST MANAGEMENT FOR DELAY TOLERANT NETWORK (20)

More from IAEME Publication (20)

Recently uploaded (20)

TRUST MANAGEMENT FOR DELAY TOLERANT NETWORK