International Journal of Engineering Trends and Technology (IJETT) – Volume 16 Number 4 – Oct 2014
Performance Evaluation of FBU-NDA Based IDS
Using AODV in MANET
TruptiAgrawal
Swati Tiwari
Research Scholar, Dept. of CSE
Oriental University
Indore (M.P), India
Associate Prof.,Dept. of CSE
Oriental University
Indore (M.P), India
Abstract— MANET is a less infrastructure network with
vigorously changing topologies and arbitrary communicating
node. At this time the mobile nodes communicate directly with
additional nodes without any router and hence the preferred
functionalities are embedded to each node. Since the
MANETconsistof mobile nodes with less configuration of
hardware and requirements compared to a router,
henceprotocols and routing used are of lightweight
functionalities. The range of protocol in MANET is categorized
in two types: Proactive and Reactive. This work deal with
enhancingMANET security through intrusion detection system
for the AODV reactive protocol. The nodes that work towards
degrading the normal network performance arecalled as
malicious or attacker nodes. The sort of traffic generated by such
node is nasty and affects the lifetime of network and other
performance factor. Also the intruder’s node aim towards
modification of actual packet information and forge them for
diverting the network traffic through these malicious nodes
which later on dropped or delayed. Hence, such intruder’s nodes
need to be identified timely for making the safe and secure
communication in the network. For the period of the last few
years, many approaches had been suggested along with several
intrusion detection systems. Though there are some problems
which remain unaddressed and are not resolved as required. In
the presence of these nodes or in delays of such detection the
network performance gets down continuously. In this idea it
proposes a novel scheme based on FBU-NDA (Feature Based
Unified Node Data Analysis) for AODV in MANET. These
scheme is capable of detecting the intruder’s node by
continuously analyzing the network parameters and getting the
acknowledgement counts. It also serves as a regular monitoring
which access the behavior of each node. Result evaluation and
comparison makes the actual assessment of the suggested
approach and proves to be improved that traditional approach.
Keywords— MANET (Mobile Ad-hoc Network), AODV (Ad-hoc
On demand Distance Vector Routing), FBU-NDA(Feature Based
Unified Node Data Analysis), IDS (Intrusion Detection System),
Performance Factors;
I.
INTRODUCTION
The wireless network is getting biggerand denser day by
day. As the number of user are increasing with recent updating
technologies. The wireless network is one of such network
having large number of support for device applications. These
networks provide mobility responsive communications within
a particular network range. A wireless network is categorized
into many subnetworks or domains supporting these
technologies such as Global service for mobile(GSM), Code
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division multiple access(CDMA), Bluetooth, ZigBee, Mobile
Network (MANET), Vehical Ad-hoc network(VANET),
Cognitive, WSN etc. Further categorization of network is
possible on the basis of dependency on device and their range
of communication distance. Entire of this network works on
radio transmission and applies through connection less
protocols and sometimes also through connection oriented
protocols. It ensures the successful data delivery to the
destination from the source.
MANET is a mobile ad-hoc network build by group of
nodes in a specific range which can communicate directly
with each another without any infrastructural requirements
such as routers, switches and cables. Hence it is known as an
infrastructure independent network. In this each node will
serve as an infrastructure support for data or transfer
instruction. There no controlling or observing power exists for
dealing with this correspondence. Rather every single node
will do the same. Here every hub acts as a switch and takes
after a static or dynamic topology, implies it is continuously
changing as the portability of hub builds. Hubs within one
another's radio range communicateespecially by means of
remote connections, while others which are located at a
distance uses different other hubs to communicate [1]. Hubs
normally disseminate the same physical media; they transmit
and secure signs at the same frequency band from the
aggregate accessible data transfer capacity, though the
transmission is simple and not indigent the system is
defenceless against the assault on the grounds that the security
component is not legitimately started in such little run system.
There are various factors which open the loose area for
attack probability like false association links for
communication between the nodes in the network,
dynamically changing topology, limited power by battery etc.
All this provides the weak zone for different kinds of attacks.
The MANET is more prone to undergo from the
intruderbehaviorcompared to the wired networks used
traditionally [2]. Thus, it is compulsory to handle such
security breaches, which are coming day by day in wireless
networks. With increasing use and applications of MANET in
market, security systems will also need to be made for each
and every condition and issues. Most of the routingprotocol in
MANET is of short range and lightweight protocol as they
need to be executed in mobile environments and hence its size
and environment must be small.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 16 Number 4 – Oct 2014
The routing protocol in MANET assumes that each node in
the network is a peer and not an intruder’s node or selfish
node. Hence, only a node that deals with a foul node can cause
the network to fall short such node is known as an intruder’s
node.Thus a security system is used to provide the security
from such intruder’s node and it is used to contantly monitor
the activity of attack exposed nodes. The system that
implement this task is known as an Intrusion Detection
System (IDS) [3]. The system architecture for MANET
regarding its functionsis both on level or multi-layer sort.
Along these lines the best reasonable system structural
engineering for a MANET build on upon its framework
prerequisites which ought to be assaulted safest.
II. RELATED STUDY
In wireless network the activity which is unauthorized
and not recognized with aim to make the normal performance
of network down comes under the category of intrusions. Such
intruder’s nodes and traffic need to be detected in early stages
of communication to make the network works normal. This
action is going to be executed on malicious node in a specific
range of communication. Different nodes can correspond all
the while alongside their directing topology redesigns at every
hub because of their portability. This framework is getting
complex & weak, which prompt most security issues.
Interruption recognition or intruder detection might be utilized
as a second level of security barrier to ensure the system from
such issues. In the event that the interruption is located, a
reaction could be started to forestall or minimize mischief to
the framework. Interruption recognition might be grouped
focused around investigating the chronicled information as
either has based or system based. A system based IDS catch
and breaks down parcels from a system activity while a hostbased IDS utilization working framework or application logs
in its dissection.
During the last few years, various authors had worked
towards improving the IDS structure, working and
functionality to achieve better goals in terms of performance,
detection rate and accuracy. This process is based on data
analysis of previous transmissions and identifying the traffic
and nodes which are violating the communication rules. To
build an efficient IDS mechanism some novel algorithms need
to be developed and will serve as core components of design
given by some rules and feature driven approaches [4]. Such
features are the combination of facilities and output of the
exacting algorithms. All the IDS has some of the common
functionalities or components which are:



Monitoring: use to monitor the nodes, neighbors or it.
Database or log file: use to record the event by
intrusion effect, make statistics and share with other
nodes.
Response: after intrusion detects, what system or
node can do in reply or response.
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Classification based intrusion detection mechanism is
given in the paper [5] using unsupervised learning methods.
Totally the approach uses five algorithms for data evaluation
and to achieve its goals multiple intermediate metrics are
created for effective transformations. The paper also deals
with tuning the classifiers for unknown type of attack which is
determined by its historical data analysis. The approach used
for this is called cross validation in which the data from the
same types of attacks are available in all fields. This differs
from real-world employment where unknown types of attacks
may be present. The identified results indicate that weighted
cost matrices can be used effectively, which developing an
anti intruder system.
For more upgrade secured a portion of the creators had
centered their worries on security methods for interruption
preventions. Among them most valuable is the encryption and
validation, whichdiminish the dangers of interruption
procedures, however, not had the capacity to uproot it totally.
Subsequently, in the paper [6], creator proposes another
quantitative technique for interruption identification which is a
behavioral oddity based framework. In this work the key
substance is the nearby IDS executor to every versatile hub.
These operators run autonomously and screen exercises of the
client and framework and correspondence exercises inside
their radio extent to identify strange conduct.
In the paper [7], a novel intrusion detection technique
based on Enhanced Adaptive Acknowledgment (EAACK) for
MANETs is proposed with right way evaluation. The paper
shows higher maliciousness detection rates indefinite
situations while does not greatly affect the network
performances and behavior. The suggested approach consisted
of three major components: ACK, secure ACK (S-ACK), and
misbehavior report authentication (MRA) scheme. In process
of distinguishing the packet types in different schemes, the
paper included a 2-b packet header in EAACK. At the primary
level of work the approach is generating effective results with
minimum load.
The paper [8], gives an intrusion detection scheme by
integrating the outcomes of two anomaly based methods:
Conformal Predictor k-nearest neighbor and Distance based
Outlier Detection (CPDOD) mechanism. The collective effect
of two anomaly mechanisms CP-KNN and DOD in a
conditional succession structure gives better result and
effective detection rates with higher accuracy in categorizing
the traffic. A chain of the tentative results shows the valuable
detection of anomalies with low false positive rate and higher
accuracy is served by simulations in a given paper.
Some of the researchers had also focused their intentions
towards the intrusion detection system containg multifunctionality. The paper [9] suggests a novel cross layer IDS
whose detection is more accurate with detection of attacks
targeted at or from source. The recommended work gives a
layered design for effective detection based on anomaly
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International Journal of Engineering Trends and Technology (IJETT) – Volume 16 Number 4 – Oct 2014
exposure by utilizing cluster data mining technique. The
proposed cross-layer based intrusion detection architecture is
designed to detect DOS attacks and sink hole attack at
different layers of the protocol stack. The approach is also
capable to detect various types of UDP flooding attack and
sink hole attack in an efficient way.
Various other approaches are proposed in the last few
years based on existing method like a regulator in [10]. As the
main advantage of it is that the watchdog only needs local
information and, therefore, it becomes quite difficult for it to
be badly influenced by another node. But it has two
disadvantages:


The watchdog is vulnerable to cooperative attacks,
and
It is not so accurate when we increase node's
mobility.
It also proposes an improvement in this mechanism which
can be used in MANET. The watchdog is a basic module for
several different IDS, making an extra effort for improving it
becomes a necessity. The proposed improvements can cope up
well with the watchdog weaknesses based on Kalman filters.
Another improvement of the approach is evidence of
collaborative black-hole attack. A secure exchange of
information among nodes allows determining whether if a
node is acting as an accomplice, and also marks it as being
malicious.
In the current paper [11], a comparison is made between
various existing IDS based on inputs, outputs, processes,
benefits and drops. After studying the various approaches and
their benefits the paper also suggested some guidelines for
selecting effective IDS for larger security. The paper also
performs few experiments to prove the comparison results and
will direct the further researches. The paper also presents a
case study of an MIS/CIS/CS curriculum on the first
introduction of the new technology for IDS in MANET.
Similarly, carrying forward the above research concern a
comparative study is developed to analyze the IDS
architectures proposed in the existing literatures [12].
Taking forward the traditional intrusion detection
mechanism some of the authors had worked with encryptions,
firewalls, etc. Thus to detect the unauthorized access to the
system in early phases of interactions the author introduces
IDAR, a signature-based Intrusion Detector dedicated to ad
hoc routing protocols. This system is going to analyze the
pattern of reuse. Result evaluation shows the limited resource
consumption (e.g., memory and bandwidth) and high detection
rate along with reduced false positives attacks [13].
III. PROBLEM DOMAIN
The intrusion detection system is a type of analysis
process that separates the trustworthy data from the intruder’s
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data. Behavior of each node in a network can be measured by
calculating the difference between data and node. Trustworthy
node which is generating the normal data can also be
sometimes taken as intruder’s node from existing intruder
detection systems. Thus the prime objective of this work is to
make the system more accurate and fast is. Because of node’s
lack of physical security, intruders can easily capture and
compromise nodes to acquire attacks [14]. Intruders can easily
compromise ad-hoc network by inserting uncooperative nodes
into the network. In such case, it is necessaryto build an
intrusion-detection system (IDS) due to the limitations of most
mobile network routing protocols, nodes in networks assume
that other nodes always cooperate with each other to relay data
[15]. After analysing the various research articles this work
had identified following area of work which remains
unaddressed by the existing intruder detection system.
With existing IDS it is very difficult to distinguish
between normal traffic and intruder’s activity traffic. Thus the
mechanism needs to be more productive to preempt those data
losses by malicious nodes. In wireless network the connection
is not static and mobile nodes can join and leave the network
at any instance of time. On behalf of instance, a node which is
in the short term out of synchronization may forward packets
that could be considered of attack activities, IDS should use
minimal resources that are not used in existing approaches.
The current IDS mechanism is not able to detect false positive
attacks and Partial drops started by an intruder’s node. Thus,
this attacks need to be blocked. Data losses and identity theft
by intruder’s nodes is generally affected by lack of central
monitoring points. Many other problems like, uncertain
collisions, recipient collisions, restricted transmission power
(Links & Resources), false misbehavior report and Collision
are the entities not been managed by existing system.
IV. PROPOSED FBU-NDASOLUTION
This paper gives a scheme to detect the malicious
misbehaving nodes having usual collisions and packet
droppings. Such node also generates the faulty misbehavior
report that they are behaving well in the network while in
reality they are harming the network performance by packet
dropping. Thus, effective and on time identification of these
nodes is necessary. Such identification is quite a tough task as
the actual traffic is been analysed and after which the
unreliable transmission is identified by comparing it with the
exiting flow pattern. Thus helps in identification of false loss
and flow. The proposed work will improve the deficiency of
existing IDS which fails to detect the false misbehaviour
timely. This work proposes a Feature Based Unified Node
Data Analysis (FBU-NDA) [16] Based IDS through AACK
for AODV protocol. It works on the basis of 4 modules. It
starts with data gathering, categorization, processing and
intimation. The above scheme is named as a FBU-NDA
because in this a feature based node characteristic is analyzed
and monitored for intruder’s identification. FBU-NDA can be
measured through a threshold for behavioral pre-emption.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 16 Number 4 – Oct 2014
Proposed Algorithms
the packets and continuously exchange these data to map the
intruder behavior identifications.
Starts Protocol AODV ()
It traces the data and circulates it into the six categories:
Hosts Counts, Behavior Analysis, and Acknowledgement
count, Neighbors count, Packet sent and received. It saves the
important details and patterns into some local data storage
area. Now, this information is passed to the next module of
FBU-NDA.
FBU-NDA ()
{
Starts New Route
Broadcast RREQ to All Neighbors
Wait for Reply Acknowledgement
If (Destination D = = Receives Packet)
{
ACK==True;
Revert RREP & ACK
}
Else
ACK==False
If (Source Rcv ACK == True && TTL==Fixed)
Packet Delivered Successfully;
Else
Pact Fails;
IDS Execute ();
{
Count ();
Performance_Based_Detection ();
Exit;
}
Count () // Definition of Function
{
Node (); // Total Number of Packets Sent & Received
Neighbor (); //Listen Neighbors Transmission
Report (); //After fixing Period of Time Nodes Give report
to FBU-NDA Node
}
FBU-NDA_Performance_Based_Detection ()
{
PDR ();
Throughput ();
Routing Overhead ()
If (PDR, Throughput, Routing Overhead < Threshold)
Intrusion detected;
}
Description:In the above proposed algorithm of FBU-NDA
[16], the intruder’s behavior in the MANET traffic can be
evaluted by the regular monitoring of performance parameters.
Initially, the network is regularly generating the data of flow
structures when the network and its transmission are started.
The host sends and receives data packets effectively by
starting the communicating with each other. The FBU-NDA
mechanism stores this report and transfer details in its
identification unit in form of log. This identification unit
continuously monitors the behavior of the each node, analyzes
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In this step the comprehensive acknowledgement node
(FBU-NDA) starts getting the details related to intruders
identification by analysis of the collected data. FBU-NDA
works as a malicious behavior identification system by
analyzing the information about packet drop by nodes and
patterns by their generated log data. The scheme uses 3 steps
for distributing the data and gathering the intruder’s behavior.
These are throughput analysis, responsecount, and analysis of
packet drop ratio. By using above steps the intruder’s behavior
is determined and intruder’s node is recognized. In FBU-NDA
processing unit, the definite data analysis is done for each and
every participating node in data transfer, so if any one of the
node is behaving uneven and making the data drops or losses
then it has to be identified. This scheme uses a threshold value
with which each node is taken as malicious or intruder’s node.
When a node is above the specific threshold value, then it is a
normal node.
V. RESULT EVALUATION
In order to measure and compare the performances of the
proposed FBU-NDA scheme, the work continues to adopt the
three performance metrics, First is Packet delivery ratio (PDR)
which defines the ratio of the number of packets received by
the destination node to the number of packets sent by the
source node. Second is Routing overhead (RO) which defines
the ratio of the amount of routing-related transmissions such
as RREQ, RREP, ACK, 2ACK, S-ACK etc. Third is the
throughput which gives the effectiveness of the systems in
transmitting the packets. The proposed mechanism can be able
to identify the attacks based on their types. This can be
prevented before any damage or packet drops. Further, it can
be extended to a few more parameters based upon the network
density. This algorithm can also be extended to identify and
avoid few more network layer attacks. To simulate proposed
approach, a scenario is created by writing TCL (Tool
Command Language) script in which fifteen nodes are created
with specified coverage and transmission power. Further
components are also clear in script file such as antenna type,
routing protocol and queue type. Every node assigns hundred
percent energy.
TABLE I
SIMULATION ENVIRONMENT
Number of nodes
Simulation time (seconds)
Radio range
Traffic type
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20
75
280m
FTP
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International Journal of Engineering Trends and Technology (IJETT) – Volume 16 Number 4 – Oct 2014
Packet size (bytes)
Transmission energy consumption
512
1.0J
Packet delivery ratio (PDR) – the ratio of the number of
packets received at the destination and the number of packets
sent by the source. In this PDR of the transmission at any
given time is calculated as,
Throughput-It is the sum of the sizes (bits) or number
(packets) of generating/sending/forwarded/received packets,
calculated at every time interval and divided by its length.
Throughput (bits) is shown in bits. Throughput (packets)
shows the numbers of packets in every time period. Time
period length is identical to one second by default.
PDR = (packets received/packets sent)
GRAPH 1: E VALUATION OF PDR ANALYSIS OF E XISTING AND PROPOSED
APPROACH
After analysis of the result of various factors of the
simulation environment, it is found that the packet delivery
ration of the proposed approach is more than the existing
approach and is shown in the above graph. It assures that after
applying the suggested approach for intrusion detection the
mechanism is capable of detecting the malicious behavior on
time and will able to reduce the drops.
Routing Overhead: In this evaluation number of routing
packets transmitted for each data packet delivered at the
destination.
GRAPH 2: E VALUATION OF ROUTING OVERHEAD ANALYSIS OF EXISTING AND
PROPOSED APPROACH
While measuring the overhead associated for suggested
scheme and the existing scheme for overall network it is found
that the proposed mechanism is acquiring less control
overhead than the existing approaches.
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GRAPH 3: C OMPARISON OF T HROUGHPUT ANALYSIS OF EXISTING AND
PROPOSED APPROACH
Another significant fact can be measured with respect to
the approach is the power consumption of the nodes in the
arrangement. After compared to other approaches, the
proposed method presents a easy one-hop acknowledgement
and one way trust record, termed as a semantic protection
mechanism, seriously reduces overhead in the traffic and the
transmission time. The overall transmission for sending and
receiving data happens in just few milliseconds, overcoming
the time constraint thereby reducing power consumption.
VI. CONCLUSION
Intruders or malicious nodes will bring great harm to the
performance of MANET. Thus to make the network more
secure and robust against these unwanted malicious node
intrusion detection system is used. This paper will study
various existing mechanisms to make some preventions
regarding these intrusions. But they have some negatives also
like timely analysis of misbehaving nodes, false identification,
collision detection, central monitoring node, partial drops, etc.
Thus this work proposes an improved IDS solution for
overcoming these issues using FBU-NDA. The work uses a
standard, centrally controlled monitoring node (FBU-NDA)
which hear the transmission of other nodes also. These
transmissions had a value compared with the standard
threshold value to classify actual & misbehaving nodes. At the
evaluation point of view the paper also presents some results
with performance parameters analysis and comparison with
existing systems. This workproved analytically that the
suggested approach is effectively improving the network
performance and is better than any of the traditional intrusion
detection approach. Also the approach makes the network
lives for more duration because of its less energy consumption
and low overheads.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 16 Number 4 – Oct 2014
FUTURE WORK
Some problems and concepts that remain unaddressed can
be performed in the future. Such as with the help of preemptive approach more information can be added for exact,
timely analysis of intrusion & its successful detection with
high accuracy. It can also be used for quantitative &
qualitative analysis, rank ordering, etc. We also embed the
source code of our proposed scheme in NS2 so as to use the
benefits of an approach like open source.
ACKNOWLEDGMENT
This research work is self-financed and recommended
from the university so as to enhance the security breaches with
current techniques in mobile ad-hoc networks using IDS.
Thus, the authors like to thank the anonymous reviewers for
their valuable comments, which strengthened the paper. The
authors also wish to acknowledgeOriental University, Indore
administration for their support & motivation during this
research. They also like to give thanks
to
Prof.JitendraChaudharyfor the discussion regarding the
situational awareness system & for producing the approach
adapted for this paper.
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