A Probabilistic Misbehavior Detection Scheme towards Efficient Trust Establishment in Delay-tolerant Networks

ABSTRACT:

Malicious and selfish behaviors represent a serious threatagainst routing in Delay/Disruption Tolerant Networks (DTNs). Due tothe unique network characteristics, designing a misbehavior detectionscheme in DTN is regarded as a great challenge. In this paper, wepropose iTrust, a probabilistic misbehavior detection scheme, for secureDTN routing towards efficient trust establishment. The basic idea ofiTrust is introducing a periodically available Trusted Authority (TA) tojudge the node’s behavior based on the collected routing evidencesand probabilistically checking. We model iTrust as the Inspection Gameand use game theoretical analysis to demonstrate that, by setting anappropriate investigation probability, TA could ensure the security ofDTN routing at a reduced cost. To further improve the efficiency ofthe proposed scheme, we correlate detection probability with a node’sreputation, which allows a dynamic detection probability determined bythe trust of the users. The extensive analysis and simulation resultsshow that the proposed scheme substantiates the effectiveness andefficiency of the proposed scheme.

EXISTING SYSTEM:

In DTNs, a node could misbehave by dropping packetsintentionally even when it has the capability to forward thedata (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 enjoyingthe services provided by DTN while refusing to forward thebundles for others, or malicious nodes that drop packets ormodifying the packets to launch attacks.

Recently, there are quite a few proposals for misbehaviorsdetection in DTNs, most of which are based onforwarding history verification (e.g., multi-layered credit, three-hop feedback mechanism, or encounter ticket), which are costly in terms of transmission overhead andverification cost. The security overhead incurred by forwardinghistory checking is critical for a DTN since expensive securityoperations will be translated into more energy consumptions,which represents a fundamental challenge in resourceconstrainedDTN.

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:

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.

ADVANTAGES OF PROPOSED SYSTEM:

Reduce the detection overhead effectively.

Improved Security.

Improved Efficiency.

Will reduce transmission overhead incurred by misbehavior detection and detect the malicious nodes effectively.

SYSTEM ARCHITECTURE:

MODULES:

System Model

Routing Model

Threat Model

Itrust Scheme

MODULES DESCRIPTION:

System Model

In this paper, we adopt the system model where weconsider a normal DTN consisted of mobile devices owned byindividual users. Each node i is assumed to have a unique IDNi and a corresponding public/private key pair. We assumethat each node must pay a deposit C before it joins thenetwork, and the deposit will be paid back after the nodeleaves if there is no misbehavior activity of the node. We assume that a periodically available TA exists sothat it could take the responsibility of misbehavior detectionin DTN. For a specific detection target Ni, TA will requestNi’s forwarding history in the global network. Therefore, eachnode will submit its collected Ni’s forwarding history to TAvia two possible approaches. In some hybrid DTNnetwork environment, the transmission between TA and eachnode could be also performed in a direct transmission manner(e.g., WIMAX or cellular networks). We argue thatsince the misbehavior detection is performed periodically, themessage 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 FirstContact routing protocol, and we assume the communicationrange of a mobile node is finite. Thus a data sender out ofdestination node’s communication range can only transmitpacketized data via a sequence of intermediate nodes in amulti-hop manner. Our misbehaving detection scheme can beapplied to delegation based routing protocols or multi-copybased routing ones, such as MaxPropand ProPHET.We assume that the network is loosely synchronized (i.e., anytwo nodes should be in the same time slot at any time).

Threat Model

First of all, we assume that each node in the networks isrational and a rational node’s goal is to maximize its ownprofit. In this work, we mainly consider two kinds of DTNnodes: selfish nodes and malicious nodes. Due to the selfishnature and energy consuming, selfish nodes are not willingto forward bundles for others without sufficient reward. Asan adversary, the malicious nodes arbitrarily drop others’bundles (blackhole or greyhole attack), which often take placebeyond others’ observation in a sparse DTN, leading to seriousperformance degradation. Note that any of the selfish actionsabove can be further complicated by the collusion of two ormore nodes.

Itrust Scheme

In this section, we will present a novel basic iTrust scheme formisbehaviordetection scheme in DTNs. The basic iTrust hastwo phases, including Routing Evidence Generation Phase and Routing Evidence Auditing Phase. In the evidence generationphase, the nodes will generate contact and data forwardingevidence for each contact or data forwarding. In the subsequentauditing phase, TA willdistinguish the normal nodes from themisbehaving 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 Schemetowards Efficient Trust Establishment inDelay-tolerant Networks”, IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2014.