A Probabilistic Misbehavior Detection Scheme towards Efficient
Trust Establishment in Delay-tolerant Networks
ABSTRACT:
Malicious
and selfish behaviors represent a serious threat against routing in
Delay/Disruption Tolerant Networks (DTNs). Due to the unique network
characteristics, designing a misbehavior detection scheme in DTN is regarded as
a great challenge. In this paper, we propose iTrust, a probabilistic
misbehavior detection scheme, for secure DTN routing towards efficient trust
establishment. The basic idea of iTrust is introducing a periodically available
Trusted Authority (TA) to judge the node’s behavior based on the collected
routing evidences and probabilistically checking. We model iTrust as the
Inspection Game and use game theoretical analysis to demonstrate that, by
setting an appropriate investigation probability, TA could ensure the security
of DTN routing at a reduced cost. To further improve the efficiency of the
proposed scheme, we correlate detection probability with a node’s reputation,
which allows a dynamic detection probability determined by the trust of the
users. The extensive analysis and simulation results show that the proposed
scheme substantiates the effectiveness and efficiency of the proposed scheme.
EXISTING SYSTEM:
In DTNs, a node could misbehave by dropping packets intentionally
even when it has the capability to forward the data (e.g., sufficient buffers
and meeting opportunities). Routing misbehavior can be caused by selfish (or
rational) nodes that try to maximize their own benefits by enjoying the
services provided by DTN while refusing to forward the bundles for others, or
malicious nodes that drop packets or modifying the packets to launch attacks.
Recently, there are quite a few proposals for
misbehaviors detection in DTNs, most of which are based on forwarding history
verification (e.g., multi-layered credit, three-hop feedback mechanism, or
encounter ticket), which are costly in terms of transmission overhead and verification
cost. The security overhead incurred by forwarding history checking is critical
for a DTN since expensive security operations will be translated into more
energy consumptions, which represents a fundamental challenge in resource constrained
DTN.
DISADVANTAGES
OF EXISTING SYSTEM:
] Malicious
and selfish behaviors represent a serious threat against routing in
Delay/Disruption Tolerant Networks (DTNs).
] Due
to the unique network characteristics, designing a misbehavior detection scheme
in DTN is regarded as a great challenge.
] Even
though the existing misbehavior detection schemes work well for the traditional
wireless networks, the unique network characteristics including lack of
contemporaneous path, high variation in network conditions, difficulty to
predict mobility patterns, and long feedback delay, have made the neighborhood
monitoring based misbehavior detection scheme unsuitable for DTNs
PROPOSED SYSTEM:
ü In
this paper, we propose iTrust, a probabilistic misbehavior detection scheme,
for secure DTN routing towards efficient trust establishment.
ü The
basic idea of iTrust is introducing a periodically available Trusted Authority
(TA) to judge the node’s behavior based on the collected routing evidences and
probabilistically checking.
ADVANTAGES
OF PROPOSED SYSTEM:
ü Reduce
the detection overhead effectively.
ü Improved
Security.
ü Improved
Efficiency.
ü Will
reduce transmission overhead incurred by misbehavior detection and detect the
malicious nodes effectively.
MODULES:
v System Model
v Routing Model
v Threat Model
v Itrust Scheme
MODULES DESCRIPTION:
System
Model
In this paper, we adopt the system model
where we consider a normal DTN consisted of mobile devices owned by individual
users. Each node i is assumed to have a unique ID Ni and a
corresponding public/private key pair. We assume that each node must pay a
deposit C before it joins the network, and the deposit will be paid back
after the node leaves if there is no misbehavior activity of the node. We assume
that a periodically available TA exists so that it could take the responsibility
of misbehavior detection in DTN. For a specific detection target Ni, TA
will request Ni’s forwarding history in the global network. Therefore,
each node will submit its collected Ni’s forwarding history to TA via
two possible approaches. In some hybrid DTN network environment, the
transmission between TA and each node could be also performed in a direct
transmission manner (e.g., WIMAX or cellular networks). We argue that since the
misbehavior detection is performed periodically, the message transmission could
be performed in a batch model, which could further reduce the transmission
overhead.
Routing
Model
We adopt the single-copy routing
mechanism such as First Contact routing protocol, and we assume the
communication range of a mobile node is finite. Thus a data sender out of destination
node’s communication range can only transmit packetized data via a sequence of
intermediate nodes in a multi-hop manner. Our misbehaving detection scheme can
be applied to delegation based routing protocols or multi-copy based routing
ones, such as MaxProp and ProPHET. We assume that the network is loosely
synchronized (i.e., any two nodes should be in the same time slot at any time).
Threat Model
First of all, we assume that each node
in the networks is rational and a rational node’s goal is to maximize its own profit.
In this work, we mainly consider two kinds of DTN nodes: selfish nodes and
malicious nodes. Due to the selfish nature and energy consuming, selfish nodes
are not willing to forward bundles for others without sufficient reward. As an
adversary, the malicious nodes arbitrarily drop others’ bundles (blackhole or
greyhole attack), which often take place beyond others’ observation in a sparse
DTN, leading to serious performance degradation. Note that any of the selfish
actions above can be further complicated by the collusion of two or more nodes.
Itrust Scheme
In this section, we will present a novel
basic iTrust scheme for misbehavior detection scheme in DTNs. The basic iTrust
has two phases, including Routing Evidence Generation Phase and Routing
Evidence Auditing Phase. In the evidence generation phase, the nodes will
generate contact and data forwarding evidence for each contact or data
forwarding. In the subsequent auditing phase, TA will distinguish the normal
nodes from the misbehaving nodes.
SYSTEM
REQUIREMENTS:
HARDWARE REQUIREMENTS:
•
System : Pentium
IV 2.4 GHz.
•
Hard Disk : 40 GB.
•
Floppy Drive : 1.44 Mb.
•
Monitor : 15 VGA
Colour.
•
Mouse : Logitech.
•
Ram : 512 Mb.
SOFTWARE REQUIREMENTS:
•
Operating system : - Windows XP.
•
Coding Language :
C#.Net.
•
Data Base :
SQL Server 2005
REFERENCE:
Haojin
Zhu, Member, IEEE, Suguo Du,
Zhaoyu Gao, Student Member, IEEE,
Mianxiong Dong, Member, IEEE,
and Zhenfu Cao, Senior Member, IEEE,
“A Probabilistic Misbehavior Detection Scheme towards Efficient Trust
Establishment in Delay-tolerant Networks”, IEEE
TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2014.
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