A dynamic approach for improving performance of intrusion detection system over manet

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A dynamic approach for improving performance of intrusion detection system over manet

  1. 1. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 61 A DYNAMIC APPROACH FOR IMPROVING PERFORMANCE OF INTRUSION DETECTION SYSTEM OVER MANET 1 Kusum Nara, 2 Aman Dureja 1 Student, Computer Science and Engineering Deptt, PDM College of Engineering, Bahadurgarh, Haryana (India) 2 Asst. Prof, PDM College of Engineering, Bahadurgarh, Haryana (India) ABSTRACT A Mobile Ad-hoc Network (MANET) is one of the busy and public networks; Because of this the network suffers from the problems of different kind of attacks. In such attacks some malicious nodes are present that falsely claim itself as a valid node. It will accept the information and will not forward the information to next nodes. Intrusion Detection System (IDS) will be used to detect such kind of attacks, but these attacks slows down the performance of IDS. To improve the performance of IDS and to handle these attacks we have presented an attack avoidance scheme. In which a preventive path will be discovered in which not attacker node will be covered. The detected path may be wider than the shortest path but will provide the higher throughput and reduce the data loss over the network. In our present work we record an interconnection table to track the communication information over the network. The INVERTED TABLE APPROACH will be used to maintain this table. Once the table will be defined, the DATA MINING APPROACH will be used to identify the attacker nodes. The work will be implemented in NS2.35 and the result analysis will be driven based on throughput and the loss analysis. Keywords: Mobile Ad-Hoc Network (MANET), routing protocol, Black Hole Attack, AODV. 1. INTRODUCTION A Mobile ad hoc network is a group of wireless mobile computers (or nodes); in which nodes collaborate by forwarding packets for each other to allow them to communicate outside range of direct wireless transmission. Ad hoc networks require no centralized administration or fixed network infrastructure such as base stations or access points, and can be quickly and inexpensively set up as needed. A MANET is an autonomous group of mobile users that communicate over reasonably slow wireless links. The network topology may vary rapidly and unpredictably over time, because the nodes are mobile. The network is decentralized, where all network activity, including discovering the topology and delivering messages must be executed by the nodes themselves. Hence routing functionality will have to be incorporated into the mobile nodes. INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY (IJCET) ISSN 0976 – 6367(Print) ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), pp. 61-81 © IAEME: www.iaeme.com/ijcet.asp Journal Impact Factor (2013): 6.1302 (Calculated by GISI) www.jifactor.com IJCET © I A E M E
  2. 2. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 62 System Architecture of MANET In our architecture, one or more pre-defined nodes act as a group controller (GC), which is trusted by all the group nodes. A GC has authority to assign resources to the nodes in MANET. This resource allocation is represented as a Key Note style credential (capability) called policy token, and it can be used to express the services and the bandwidth a node is allowed to access. They are cryptographically signed by the GC, which can be verified any node in the MANET. When a node (initiator) requests a service from another MANET node (responder) using the policy token assigned to the initiator, the responder can provide a capability back to the initiator. This is called a network capability, and it is generated based on the resource policy assigned to the responder and its dynamic conditions. Figure gives a brief overview of our system. All nodes in the path between an initiator to a responder (i.e., nodes relaying the packets) enforce and abide by the resource allocation encoded by the GC in the policy token and the responder in the network capability. The enforcement involves both accessibility and bandwidth allocation. A responder accepts packets (except for the first one) from an initiator only if the initiator has authorization to send, in the form of a valid network capability. It accepts the first packet only if the initiator’s policy token is included. An intermediate node will forward the packets from a node only if the packets have an associated policy token or network capability, and if they do not violate the conditions contained therein. Possession of a network capability does not imply resource reservation; they are the maximum limits a node can use. Available resources are allocated by the intermediate nodes in a fair manner, in proportion to the allocations defined in the policy token and network capability. The capability need not be contained in all packets. The first packet carries the capability, along with a transaction identifier (TXI) and a public key. Subsequent packets contain only the TXI and a packet signature based on that public key. Intermediate nodes cache policy tokens and network capabilities in a capability database, treating them as soft state. A capability database entry contains the source and destination addresses, TXI, the capability, public key for the packet signature and packet statistics Figure 1: MANET System Architecture
  3. 3. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 63 1.1 Key Issues in MANETs Many issues can be addressed in the context of MANETs. Here some important issues are presented that have dominated the field of research since the evolution of MANETs. A. Static Datasets In MANET, the mining work is generally performed on a static confined datasets. In this the support and confidence values are defined statically. B. Ineffectiveness The existing work is ineffective if two malicious nodes will build the path and perform a fake communication. C. Cooperativeness MANET routing protocols are usually highly cooperative. This can make them the target of new attacks. For example, a node can pose as a neighbour to the other nodes and participate in decision mechanisms, possibly affecting significant parts of the network. D. Mobility MANET nodes can leave and join the network and move independently, so the network topology can change frequently. The highly dynamic operation of a MANET can cause traditional techniques of IDS to be unreliable. E. Lack of Central Points MANETs do not have any entry points such as routers, gateways, etc. These are typically present in wired networks and can be used to monitor all network traffic that passes through them. A node of a mobile ad hoc network can see only a portion of a network: the packets it sends or receives together with other packets within its radio range. Since wireless ad hoc networks are distributed and cooperative, the intrusion detection and response systems in MANETs may also need to be distributed and cooperative and this leads to some difficulties. 2. RELATED WORK Xiao Yang Zhang performed a work," Proposal of a Method to Detect Black Hole Attack in MANET". Author propose a new detection method based on checking the sequence number in the Route Reply message by making use of a new message originated by the destination node and also by monitoring the messages relayed by the intermediate nodes in the route. Computer simulation results demonstrate that Presented method has a feature of much lower false positive and negative rates in detecting any number of malicious nodes than the conventional methods. After Xiao Yang Zhang , Satoshi Kurosawa performed a work," Detecting Black hole Attack on AODV-based Mobile Ad Hoc Networks by Dynamic Learning Method" in 2007. The Author analyzes the black hole attack which is one of the possible attacks in ad hoc networks. In this paper, Author proposes an anomaly detection scheme using dynamic training method in which the training data is updated at regular time intervals. The simulation results show the effectiveness of Presented scheme compared with conventional scheme. In Year 2009, Mehdi Kargar performed a work," Truthful and Secure Routing in Ad Hoc Networks with Malicious and Selfish Nodes". Author study routing in ad hoc and wireless networks from a game theoretic view point. Based on this view, the network consists of selfish and greedy nodes who accept payments for forwarding data for other nodes if the payments cover their individual costs incurred by forwarding data. In this work, Author considers that the network consists of malicious nodes too. After Mehdi Kargar, Athira.M.Nambiar performed a work,” Wireless Intrusion Detection Based on Different Clustering Approaches” in 2010. The Author finding optimal set of features from collected WLAN data using a Ranking Algorithm technique. Then with the aid of different data mining techniques such as K-Means, self organizing map and decision tree, these features are analyzed and the performance comparison is carried out. After Athira.M.Nambiar, Rajib Das performed a work," Security Measures for Black Hole Attack in MANET: An Approach" in the year 2011. The Author gives an algorithmic approach to focus on analyzing and improving the security of AODV, which is one of the popular routing protocols for
  4. 4. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 64 MANET. Presented aim is on ensuring the security against Black hole attack. The proposed solution is capable of detecting & removing Black hole node(s) in the MANET at the beginning. In Year 2012, Saurbh Goyal performed a work," An Improved Inverted table Approach to Detect Selfish Node In Mobile Ad Hoc Network" after Rajib Das. Authors have to find the frequency of different node and group nodes over the network. To perform the frequency analysis the improved Inverted table will be used. As the selfish node will be identified the network throughput will be improved. 3. APPROACHES USED A number of different approaches have been used to detect and remove malicious nodes. We will use two major approaches to detect and remove the malicious nodes. One is The Inverted Table based approach and other is Data Mining approach. Inverted Table approach is used to define communication table with improved information management. Data mining approach is used to identify the black hole and to perform communication over the safe path. 3.1 Inverted Table Approach Inverted matrix is the numerical representation of a string. The rows of the matrix represent the various characters present in the string and are indexed in the order in which they appear in the string. In this proposed we have taken a sequence. The complete work is divided in three steps:- i. Identification of Node Sequence ii. Build the Inverted Table for the Specific Node Sequence. iii. Frequent Pattern Identification 3.2 Data Mining Approach There are basically three data mining approaches for detecting malicious nodes. They are: i. Anomaly-based Intrusion Detection approach ii. Misuse-based Intrusion Detection approach iii. Specification-based Intrusion Detection approach The first technique is anomaly-based intrusion detection approach. It profiles the symptoms of normal behaviors of the system such as usage frequency of commands, CPU usage for programs, and the like. It detects intrusions as anomalies, i.e. deviations from the normal behavior. Misuse-based intrusion detection approach compares known attack signatures with current system activities. It is generally preferred by commercial IDSs since it is efficient and has a low false positive rate. The drawback of this approach is that it cannot detect new attacks. The last technique is specification-based intrusion detection approach. In this approach, a set of constraints on a program or a protocol are specified and intrusions are de-tected as runtime violations of these specifications. It is introduced as a promising alternative that combines the strengths of anomaly- based and misuse-based detection techniques and providing detection of known and unknown attacks with a lower false positive rate. It can detect new attacks that do not follow the system specifications. 3.3 Objectives • The main objective of the work is to identify a safer path over the mobile network that will not transfer data through any black hole node. The obtained path may be wider but much safer then existing shortest path. • In this work, a new legitimacy table is proposed with improved information management. Here the association will be maintained in terms of frequency count, throughput analysis and response time analysis between different nodes. • A Mining scheme is suggested in this work based on legitimacy table to identify the black hole and to perform communication over the safe path. • The objective of work is to improve the network throughput and decrease the data loss over the network.
  5. 5. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 65 3.4 Source of Data • The main objective of the work is to identify a safer path over the mobile network that will not transfer data through any malicious node. The obtained path may be wider but much safer then existing shortest path. • In this work, an inverted list based approach is suggested to define communication table with improved information management. Here the association will be maintained in terms of frequency count, throughput analysis and response time analysis between different nodes. • A Mining scheme is suggested in this work based on invereted table to identify the black hole and to perform communication over the safe path. • The objective of work is to improve the network throughput and decrease the data loss over the network. 3.5 Research Design The proposed work is about to find the most frequent moving pattern over the network so that we can find the nodes or the nodes pair that should get the maximum concern respective to the resource allocation. The complete Research Design is given as Figure 2: Flowchart of Work Establish the Mobile Network Analyze the network in terms of forwarding, receiving and transmitting packets Define the legitimacy table to maintain communication information Identify the frequency analysis of each node over the network Find the Statistical respective to different parameters Perform the decision making based on support and confidence analysis Perform the Communication over the network Detect the black node and mark them as unsafe node Build the new Communicating path with higher reliability
  6. 6. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 66 4. ROUTING PROTOCOLS The primary goal of routing protocols in ad-hoc network is to establish optimal path (min hops) between source and destination with minimum overhead and minimum bandwidth consumption so that packets are delivered in a timely manner. A MANET protocol should function effectively over a wide range of networking context from small ad-hoc group to larger mobile networks. Classification of routing protocols in mobile ad hoc network can be done in many ways, but most of these are done depending on routing strategy and network structure. The routing protocols can be categorized as flat routing, hierarchical routing and geographic position assisted routing while depending on the network structure. According to the routing strategy routing protocols can be classified as Table-driven and on-demand. Figure 3: Ad-Hoc Routing Protocol 4.1 flat routing protocols Flat routing protocols are divided mainly into two classes; the first one is proactive routing (table driven) protocols and other is reactive (on-demand) routing protocols. One thing is general for both protocol classes is that every node participating in routing play an equal role. They have further been classified after their design principles; proactive routing is mostly based on LS (link-state) while on-demand routing is based on DV (distance-vector). 4.1.1 Pro-Active/Table Driven routing Protocols Proactive MANET protocols are also called as table-driven protocols and will actively determine the layout of the network. Through a regular exchange of network topology packets between the nodes of the network, at every single node an absolute picture of the network is maintained. There is hence minimal delay in determining the route to be taken. 4.1.2 Reactive (On Demand) protocols Portable nodes- Notebooks, palmtops or even mobile phones usually compose wireless ad- hoc networks. This portability also brings a significant issue of mobility. This is a key issue in ad- hoc networks. The mobility of the nodes causes the topology of the network to change constantly. Keeping track of this topology is not an easy task, and too many resources may be consumed in signaling. Reactive routing protocols were intended for these types of environments.
  7. 7. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 67 4.2 Hierarchical protocols These protocols include HSR, ZRP, CGSR, LANMAR protocols. 4.3 Geographic position assisted or Hybrid protocols Hybrid protocols make use of both reactive and proactive approaches. Example of this type includes Zone Routing Protocol (ZRP), ZHLS etc. 5. AN OVERVIEW OF AODV ROUTING PROTOCOL Ad hoc On Demand Distance Vector Routing (AODV) Ad hoc On-Demand Distance Vector (AODV) routing is a routing protocol for mobile ad hoc networks and other wireless ad-hoc networks. It is jointly developed in Nokia Research Centre of University of California, Santa Barbara and University of Cincinnati by C. Perkins and S. Das. It is an on-demand and distance-vector routing protocol, meaning that a route is established by AODV from a destination only on demand. AODV is capable of both unicast and multicast routing. It keeps these routes as long as they are desirable by the sources. Additionally, AODV creates trees which connect multicast group members. The trees are composed of the group members and the nodes needed to connect the members. The sequence numbers are used by AODV to ensure the freshness of routes. It is loop-free, self-starting, and scales to large numbers of mobile nodes. AODV defines control messages for route maintenance such as: RREQ- A route request message is transmitted by a node requiring a route to a node. As an optimization AODV uses an expanding ring technique when flooding these messages. Every RREQ carries a time to live (TTL) value that states for how many hops this message should be forwarded. This value is set to a predefined value at the first transmission and increased at retransmissions. Retransmissions occur if no replies are received. Data packets waiting to be transmitted (i.e. the packets that initiated the RREQ). Every node maintains two separate counters: a node sequence number and a broadcast_ id. The RREQ contains the following fields Source Address, Broadcast ID, Source Sequence no., Destination Address, Destination Sequence no., Hop count. Whenever a node needs to send a packet to a destination for which it has no ‘fresh enough’ route (i.e., a valid route entry for the destination whose associated sequence number is at least as great as the ones contained in any RREQ that the node has received for that destination) it broadcasts a route request (RREQ) message to its neighbors. Each node that receives the broadcast sets up a reverse route towards the originator of the RREQ (unless it has a ‘fresher’ one).When the intended destination (or an intermediate node that has a ‘fresh enough’ route to the destination) receives the RREQ, it replies by sending a Route Reply (RREP). It is important to note that the only mutable information in a RREQ and in a RREP is the hop count (which is being monotonically increased at each hop). The RREP travels back to the originator of the RREQ (this time as a unicast). At each intermediate node, a route to the destination is set (again, unless the node has a ‘fresher’ route than the one specified in the RREP). In the case that the RREQ is replied to by an intermediate node (and if the RREQ had set this option), the intermediate node also sends a RREP to the destination. In this way, it can be granted that the route path is being set up bi-directionally. In the case that a node receives a new route (by a RREQ or by a RREP) and the node already has a route ‘as fresh’ as the received one, the shortest one will be up dated. The source node starts routing the data packet to the destination node through the neighboring node that first responded with an RREP. The AODV protocol is vulnerable to the well-known black hole attack.
  8. 8. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 68 5.1 Black Hole Attack The black hole attack is an active insider attack, it has two Properties: first, the attacker consumes the intercepted packets without any forwarding. Second, the node exploits the mobile ad hoc routing protocol, to advertise itself as having a valid route to a destination node, even though the route is spurious, with the intention of intercepting packets. In other terms, a malicious node uses the routing protocol to advertise as having the shortest path to nodes whose packets it wants to intercept. In the case of AODV protocol, the attacker listens to requests for routes. When the attacker receives a request for a route to the target node, the attacker creates a reply where an extremely short route is advertised, if the reply from malicious node reaches to the requesting node before the reply from the actual node, a fake route has been created. Once the malicious device has been able to insert itself between the communicating nodes, it is able to do anything with the packets passing between them. It can choose to drop the packets to form a denial- of-service attack. Figure 4: Black Hole Attack 5.2 Algorithmic approach to avoid black hole attack in MANETs Algorithm() { 1. Perform the Randomized placement of nodes under defined parameters 2. Define the multiple sources called S1,S2…Sn 3. Define Multiple Destination Nodes called d1,D2…..Dm 4. Define the Minimum Throughput Support and Confidence called EffectiveSupport and EffectiveConfidence. Also define supportdelay and confidencedelay 5. For i=1 to n 6. { For j=1 to m 7. { Perform communication between each pair S(i) and D(j) 8. Identify the Intermediate communication nodes between each pair nodes called Node1,Node2…Node k 9. Estimate the Association mining between each intermediate node under different Parameters for all k nodes called Throughput, Idle Rate and the network delay etc. 10. If(Throughput(Node(i))>EffectiveSupport Delay(Node(i))<supportdelay)
  9. 9. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 69 11. { If(Throughput(Node(i))> Throughput(Node(i+1) And IdleRate(Node(i))> IdleRate(Node(i+1)) 12. { 13. If(Throughput(Node(i))>EffectiveConfidence And Delay(Node(i))<confidencedelay) 14. { Set Node(i) as Valid Path Node 15. } 16. Else if(Throughput(Node(i))>EffectiveConfidence) 17. { Set Node(i) as Valid Path Node 18. } 19. Else 20. { Reconsider Node(i) if No node is under confidence level 21. } 22. } 23. Else 24. { Avoid Node (i) from path 25. } 26. } 27. } 28. } 29. } Example Let we have seven nodes and the communication between the nodes is defined in terms of one to one data transmission between the nodes. If the nodes have communication it will be represented by 1 else it will be represented by 0. Sample DataSet A B C D E F G 1 1 0 0 0 1 1 1 1 1 1 1 1 0 1 1 0 0 1 1 1 1 1 0 0 0 0 0 1 0 1 0 0 0 0 1 1 1 0 0 0 0 1 0 0 0 0 0 0 Table 1: Sample Data In this table a sample dataset is shown with 7 nodes with communication. The value 1 here represents the transmission of data and 0 represents the absence of transmission. From this dataset we drive a table of existing dataset.
  10. 10. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 70 {A} 7 {A} & {B} 5 {A} & {C} 3 {A} & {D} 1 {B} & {D} 1 {C} & {D} 1 Table 2: Association of Data In this table some association are shown here with the occurrence of values in different attributes. In same way all the possible association will be taken. On the analysis of this association a lower threshold value will be defined such as 2. Now all the association having support less then this defined value will be eliminated. Now the attribute with minimum support will be eliminated from the dataset. In such way the incomplete information fields and the non required fields and record set will be eliminated and incomplete data impurities will be eliminated. If the confidence value is 70% then the value 5 will be valid for the communication. It means A and B are most associated nodes. Results Scenario Figure 5: Scenario
  11. 11. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 71 Figure 6: Packet transmission 6. PERFORMANCE EVALUATION In this section, we concentrate on describing our simulation Environment and methodology .To implement the above defined work we have used the NS2.35 as the simulation environment. A. Network Simulator NS-2 is an open-source simulation tool running on Unix-like operating systems. It is a discreet event simulator targeted at networking research and provides substantial support for simulation of routing, multicast protocols and IP protocols, such as UDP, TCP, RTP and SRM over wired, wireless and satellite networks. It has many advantages that make it a useful tool, such as support for multiple protocols and the capability of graphically detailing network traffic. Additionally, NS-2.35 supports several algorithms in routing and queuing. LAN routing and broadcasts are part of routing algorithms. Queuing algorithm includes fair queuing, deficit round robin and FIFO. NS-2 started as a variant of the REAL network simulator in 1989. REAL is a network simulator originally intended for studying the dynamic behavior of flow and congestion control schemes in packet-switched data networks. In 1995 ns development was supported by Defense Advanced Research Projects Agency DARPA through the VINT project at LBL, Xerox PARC, UCB, and USC/ISI. The wireless codes from the UCB Daedelus and CMU Monarch projects and Sun Microsystems have added the wireless capabilities to ns-2.35. Simulation Parameters As already outlined, in this proposed system we will observe the actual throughput in shortest path and alternate path. Firstly analyze the network detect if there is some misbehaving node based on the current statistics of receiving packets, forwarding packets and dropping packets. Now the data will be transferred from some compromising node.
  12. 12. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 72 The needed Parameters to carry out the simulation and their corresponding values for both protocols are specified below: Parameter Value Number of Nodes 36 Topography Dimension 800 m x 800 m Traffic Type CBR Radio Propagation Model Two-Ray Ground Model MAC Type 802.11.Mac Layer Packet Size 512 Mobility Model Random Way Point Antenna Type Omni directional Protocol AODV Table 3: Simulation Parameters In Table 3, the mobile ad hoc network comprising of 50 mobile nodes is constructed in the NS-2 simulator with the use of TCL script in the topological boundary area of 670 m x 670 m. The position of the mobile nodes is defined in terms of X and Y coordinates values and it is written in the movement scenario file. A NS2 application will be used to generate sample data. Care will be taken to make sure that the approach is tested for performance considerations under similar hardware and software environments. To test the performance of all of the above stated approaches, a program is written in TCL and tested in real environment. Simulation in NS2 The ad hoc network comprising of 25 nodes is constructed in the NS-2 simulator with the use of ETCL script in the topological boundary area of 1050 m x 100 m. The position of the mobile nodes is defined in terms of X and Y coordinates values. The given scenario showing the packet transmission with shortest path between the nodes starting from the source node 0 to the destination node 9. Figure 7: Placement of Nodes
  13. 13. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 73 Figure 8: Communication over the network 1) NS2.35 Overview The network simulator (NS), which is a discrete event simulator for networks, is a simulated program developed by VINT (Virtual Internetwork Test-bed) project group. It supports simulations of TCP and UDP, some of MAC layer protocols, various routing and multicast protocols over both wired and wireless network etc. Depending on user’s requirement the simulation are stored in trace files, which can be fed as input for analysis by different component: • A NAM trace file (.nam) is used for the ns animator to produce the simulated environment. • A trace file (.tr) is used to generate the graphical results with the help of a component called X Graph. When the simulation is finished, the simulation results are produced in one or more text- based output files that contain detailed simulation data, which can be used to analyze directly or can be used in the graphical user interface Network Animator (NAM). This graphical user interface shows the simulation result in an easy way. The language that is written in NS-2.35 is not only OTcl but also C++. The event scheduler and the basic network component objects in the data path are written and compiled using C++ to reduce packet and event processing time.These compiled objects need the OTcl linkage to create a matching OTcl object for each of the C++ objects to be able to work with OTcl interpreter. 2) Tool Command Language (Tcl) Tool Command Language, Tcl is a powerful interpreted programming language developed by John Ouster out at the University of California, Berkeley. Tcl is a very powerful and dynamic programming language. It has a wide range of usage, including web and desktop applications, networking, administration, testing etc. Tcl is a truly cross platform, easily deployed and highly extensible. The most significant advantage of Tcl language is that it is fully compatible with the C programming language and Tcl libraries can be interoperated directly into C programs. 3) Network Animator (NAM) The biggest advantage of network animator (NAM) is that it provides a graphical user interface (GUI) for the different simulation environment according to the parameters specified by the user. The Xgraph utility generates the graphical output of the input data (or trace files).
  14. 14. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 74 To animate network traffic in several ways, nam interprets a trace file containing time-indexed network events, as Figure 3(a) shows. Typically, an ns simulation generates this trace, but nam can also use processing data from a live network to produce a trace. 6.2 Simulation Results Figure 8.1: Network Design Here figure 8.1 is showing the network design for the given work. The network is here created with 36 nodes. Figure 8.2: Network Communication Here figure 8.2 is showing the communication over the network. As we can see, there the communication is performed between three node pairs at the same time. The network is also giving the packet loss because of attacked nodes over the network.
  15. 15. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 75 6.3 Analysis Results Figure 8.3: Packet Transmitted (Existing vs. Proposed Approach) Here figure 8.3 is showing the comparative analysis of packet transmitted over the network. Here x axis represents the time and y axis represents the packet transmitted. As we can see after implementing the proposed approach the successful packet transmission over the network is increased.
  16. 16. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 76 Figure 8.4: Packet Lost (Existing vs. Proposed Approach) Here figure 8.4 is showing the comparative analysis of packet lost over the network. Here x axis represents the time and y axis represents the packet transmitted. As we can see after implementing the proposed approach the packet loss over the network is decreased.
  17. 17. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 77 Figure 8.5: Bytes transmitted (Existing vs. Proposed Approach) Here figure 8.5 is showing the comparative analysis of bytes transmitted over the network. Here x axis represents the time and y axis represents the bytes transmitted. As we can see after implementing the proposed approach the bytes transmitted over the network is increased. Figure 8.6: Bit rate (Existing vs. Proposed Approach) Here figure 8.6 is showing the comparative analysis of bit rate over the network. Here x axis represents the time and y axis represents the bit rate of communication. As we can see after implementing the proposed approach the bit rate over the network is increased
  18. 18. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 78 Figure 8.7: Packet Delay (Existing vs. Proposed Approach) Here figure 8.7 is showing the comparative analysis of Packet Delay over the network. Here x axis represents the time and y axis represents the Packet Delay of communication. As we can see after implementing the proposed approach the Packet Delay over the network is decreased.
  19. 19. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 79 Figure 8.8: Packet Loss rate (Existing vs. Proposed Approach) Here figure 8.8 is showing the comparative analysis of Packet Loss rate over the network. Here x axis represents the time and y axis represents the Packet Loss rate of communication. As we can see after implementing the proposed approach the Packet Loss rate over the network is increased.
  20. 20. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 80 6. CONCLUSION AND FUTURE WORK 6.1 Conclusion The proposed work is about to generate a preventive path to avoid the communication over a faulty node or on congested node. The proposed work is about to improve the AODV protocol in terms of security. As in case of multicast network because of lot of communication the network suffers from some attack that results the packet loss over the network. The proposed work is about to minimize this packet loss over the network. The work will increase the throughput with this improved AODV protocol. The system is providing better throughput and less packet loss over the network. The system is implemented in a wireless network with AODV protocol. In this system a Table based data mining approach is defined to perform the analysis among neighboring nodes and to provide the communication from effective path. Here we have proposed a new algorithm for the above said task. The implementation is performed in ns2 and analysis is presented using Xgraph. 6.2 Future Scope The proposed system can be enhanced in future by other researchers in the following ways • We have worked only with AODV protocol. The work can be implemented and analyzed along with other protocols. • We have performed the work only with Black hole Node attack, the work can be enhanced by implementing some other attack such as wormhole, flooding attacks, DOS etc. • We have presented the work with a Legitimacy Table approach in a wireless network. The work can be implemented on some specific network such as PAN, WiMax etc. 7. REFERENCES [1] Satoshi Kurosawa," Detecting Blackhole Attack on AODV-based Mobile Ad Hoc Networks by Dynamic Learning Method", International Journal of Network Security, Vol.5, No.3, PP.338– 346, Nov. 2007 (pp 338-346) [2] Vera Marinova-Boncheva," Applying a Data Mining Method for Intrusion Detection", International Conference on Computer Systems and Technologies - CompSysTech’07 [3] Zahra Safaei," An Efficient Reputation-Based Mechanism to Enforce Cooperation in MANETs", LATEST TRENDS on COMMUNICATIONS and INFORMATION TECHNOLOGY ISSN: 1792-4316 ISBN: 978-960-474-207-3 (pp 33-38) [4] Tsong Song Hwang," A Three-tier IDS via Data Mining Approach", MineNet’07, June 12, 2007, San Diego, California, USA. ACM 918-1-59593-792-6/07/0006 (pp 1-6) [5] LTC Bruce D. Caulkins," A Dynamic Data Mining Technique for Intrusion Detection Systems", (pp 148-153) [6] Neil Hurley," Statistical Attack Detection", RecSys’09, October 23–25, 2009, New York, New York, USA. ACM 978-1-60558-435-5/09/10 (pp 149-156) [7] Guanhua Yan," Towards a Bayesian Network Game Framework for Evaluating DDoS Attacks and Defense", CCS’12, October 16–18, 2012, Raleigh, North Carolina, USA.ACM 978-1-4503- 1651-4/12/10. (pp 553-566) [8] Yu Liu," A Bayesian Game Approach for Intrusion Detection in Wireless Ad Hoc Networks", GameNets’06, October14, 2006, Pisa, Italy. ACM 1-59593-507-X/06/10 [9] Joseph Mocker and Scott Carson Mobile ad-hoc networks (MANET). http://www.ietf.org/proceedings/01dec/183.htm. [10] J. Kong, X. Hong and M. Gela, “ A new set of passive routing attacks in mobile ad-hoc networks” in IEEE Military Communications Conference, vol. 2, pp. 796 – 801,2003. [11] www.itrainonline.org/04_en_mmtk_wireless_basic-infrastructuretopology_slides.pdf [12] F. Stajano, F. and R. Anderson, “ The Resurrecting Duckling : Security Issues For Ad-hoc Wireless Networks In Security Protocols”, 7th International Workshop Proceedings,1999.
  21. 21. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 81 [13] Y.C.Hu,A. Perrig, and D. B. Johnson, “Rushing attacks and defense in wireless Ad-hoc network routing protocols”, In Proceedings of the ACM Workshop 2003. [14] G. M. Ignas, M. Niemegeers, Sonia M. Heemstra de Groot, “Research issues in ad hoc distributed personal networking”, wireless personal communications : An international journal, vol.26, no. 2-3, pp.149-167, Kluwer Academic Publishers, August 2003. [15] G. S. Mamatha and Dr. S. C. Sharma “Analyzing the MANET Variaitons, Challenges, Capacity and Protocol Issues”, International Journal of Computer Science & Engineering Survey (IJCSES), Vol. 1, no.1, August 2010. [16] A. D.Wood and J. A. Stankovic, “Denial of service in sensor networks”,Computer, vol. 35, no. 10, pp. 54-62, 2002. [17] Hao Yang, Haiyun Luo, Fan Ye, Songwu Lu, Lixia Zhang, “ Security in mobile ad- hoc networks : challenges and solutions ”, IEEE Wireless Communications, February 2004. [18] I. Aad, J. , P. Hubaux , and E. W. Knightly, “Denial of service resilience in ad hoc network”, In Proceedings of the 10th annual international conference on Mobile computing and networking. New York, NY, USA: ACM Press, pp. 202-215, 2004. [19] Y. Xue and K. Nahrstedt, “ By passing misbehaving nodes in ad hoc routing ,” Tech. Rep.,Department of Computer Science, University of Illinois at Urbana Champaign, November 2002. [20] C. Siva Ram Murthy and B. S. Manoj, “Ad Hoc Wireless Networks, Architectures and protocol”, Second Edition, Low price Edition, Pearson Education, 2007. [21] Priyanka Goyal, Viniti parmar and Rahul Rishi, “ MANET: Vulnerabilities, Challenges,Attacks, Application”, IJCEM (International Journal of Computational Engineering & Management), Vol. 11, January 2011. [22] Irshad Ullah, “ Analysis of Black Hole Attack on MANETs Using Different MANET Routing Protocols”, Master Thesis, Blekinge Institute of Technology, June 2010. [23] Piyush Agrawal and R. K. Ghosh “Cooperative Black and Gray Hole Attacks in Mobile Ad Hoc Networks”, Indian Institute of Technology, Kanpur - 208 016, INDIA. [24] J. Bellardo and S. Savage, “802.11 denial-of-service attacks: real vulnerabilities and practical solutions”, In Proceedings of the 12th conference on USENIX Security Symposium,Berkeley, CA, USA: USENIX Association, 2003. [25] L. Zhou and Z. Haas, “Securing Ad Hoc Networks”, IEEE Networks Special Issue on Network Security, pp 24-30, November 1999. [26] S. Bansal and M. Baker, “Observation-based Cooperation Enforcement in Ad Hoc Network”, july 2003. http://arxiv.org/pdf/cs.NI/0307012. [27] Po-Wah Yau and Chris J. Mitchell, “Reputation methods for routing security for mobile ad hoc network” http://www.isg.rhul.ac.uk/~cjm/rmfrsf.pdf. [28] Michiardi P, Molva R. “ Core : a collaborative reputation mechanism to enforce node Corporation in Mobile Ad Hoc Networks ”, In Proceeding of the sixth IFIP Conf. on Security Communications and Multimedia (CMS), 2002. [29] Q. He, D. Wu, P. Khosla, “ SORI : A secure and objective reputation - based incentive Scheme For ad hoc networks ”, IEEE Wireless Communications and Networking conference 2004. [30] Manel Guerrero Zapata, “ Secure ad hoc on-demand distance vector (SAODV) routing”, draft-querrero-manet-saodv-03, Mobile Ad Hoc Networking Working Group, March 2005. [31] Syeda Gauhar Fatima, Dr. Syed Abdul Sattar and Dr.K.Anita Sheela, “Energy Efficient Intrusion Detection System for WSN”, International Journal of Electronics and Communication Engineering & Technology (IJECET), Volume 3, Issue 3, 2012, pp. 246 - 250, ISSN Print: 0976- 6464, ISSN Online: 0976 –6472. [32] Poonam Pahuja and Dr. Tarun Shrimali, “Routing Management for Mobile Ad-Hoc Networks”, International Journal of Computer Engineering & Technology (IJCET), Volume 4, Issue 3, 2013, pp. 464 - 468, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.

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