Characterizing the Impact of Black-Hole Attacks on Elastic and Inelastic applications in MANETs

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1 Characterizing the Impact of Black-Hole Attacks on Elastic and Inelastic in MANETs Tania Nagpal, Krishan Kumar M. Tech Research Scholar, Associate Professor SBS State Technical Campus, Ferozepur Punjab, India Abstract - Security in Mobile Adhoc Networks (MANETs) is a critical issue. MANETs are vulnerable to different types of attacks. Many of the routing attacks have been identified at network layer such as black hole, worm hole, gray hole and byzantine attacks. Out of all these attacks, black hole is the most important attack which disrupts the network performance severely. Most of the researchers have analyzed the impact of black hole attacks using throughput, packet delivery ratio and delay however, they have not considered number of packets dropped, jitter and many other performance metrics. Most of them have used CBR application for performing analysis. However, in MANETs a variety of Elastic i.e. FTP, HTTP, TELNET and Inelastic i.e. CBR, VBR, LOOKUP are applicable. So characterizing the impact on elastic and inelastic using jitter, delay, packet delivery ratio, number of packets dropped and throughput is very important. Index Terms - MANETs, Elastic, Inelastic, Black hole Attack, AODV (Adhoc on demand Vector Routing Protocol) I. INTRODUCTION MANETs communicate in a standalone fashion. Each node can behave as a router as well as a network user. That s why MANETs are attractive for many such as disaster relief, emergency operations, military service, maritime communications, vehicle networks, casual meetings, campus networks, robot networks etc [1]. Another characteristic of a MANETs are, they don t have any infrastructure, predefined topology and centralized administration. Due to these unique characteristics, MANETs are more vulnerable to attacks as compared to wired networks [2]. which the main motive of the attacker is to disrupt the performance of network by destroying the data during an exchange in the network. Passive attacks are those in which attacker listens to the network, i.e. how different nodes are communicating on the network instead of disrupting the normal operation of the network.[3] MANETs are inherently prone to many of the security attacks, the black hole attack is one of these. A black hole node advertises itself with a higher sequence number indicating that it has fresh route towards the destination. So it is important to study the impact of black hole attacks on various in MANETs. This paper highlights various security issues in MANETs and specifically concentrating on black hole attacks. Elastic and Inelastic are identified along with their requirements in MANETs. The impact of the black hole have been analysed on Elastic and Inelastic. Analysis of which application suffers the most due to black hole attack. The rest of the paper is organized as follows. Section II focuses on some challenges in securing MANETs. SECTION III identifies the various elastic and inelastic in MANETs. Section IV depicts the working of Black hole attacks. SECTION V gives the review of existing work. Section VI concentrates on simulation and results.final Section VII concludes the paper. II. CHALLENGES IN SECURING MANETs MANETs routing protocol suffers from many of such attacks. Existing attacks on MANETs can be classified into two broad categories based upon their nature i.e. active and passive attacks. Active attacks are those in Security is a major issue in MANETs and is very difficult to maintain it in wireless networks as compared to the wired networks. The unique characteristics of 1

2 adhoc Networks have made security a big challenge. Vulnerability in MANETs include: a) Dynamically changing network topology: Mobile nodes join and leave the network arbitrarily, resulting to dynamic change of network topology. This allows a malicious node to join the network without prior detection [4]. b) Lack of centralized monitoring: There is absence of any centralized infrastructure that prohibits any monitoring mechanism in the network. This makes the classical security solutions based on certification authorities and on-line servers inapplicable. Even the trust relationships among individual nodes also changes, especially when some nodes are found to be compromised. Hence, security mechanisms need to be on the dynamic and not static [4]. c) Cooperative algorithms: MANET routing algorithms require mutual trust between neighboring nodes, which violates the principles of network security [4]. d) The absence of a certification authority. e) The limited physical protection of each of the nodes: network nodes usually do not reside in physically protected places, such as locked rooms. Hence, they can more easily be captured and fall under the control of an attacker [4]. f) The intermittent nature of connectivity [4]. III ELASTIC AND INELASTIC APPLICATIONS The security in adhoc wireless networks is an important issue. The absence of any central mechanism makes MANETs more vulnerable to attacks as compared to wired networks. So its important, to study its impact on other also such as Elastic and Inelastic instead of analyzing it specifically on one application. Elastic are generally TCP based. They can easily adjust, over wide ranges, to changes in delay and throughput across an internet and still meet the needs of its. That s why they are said to be network friendly, for example: HTTP, FTP and TELNET. The services required by Elastic are: 1. Bandwidth: Elastic can work efficiently over whatever bandwidth is available. 3. Delay: Some application require low delay to be effective, no upper bound on delay is required here. Inelastic Applications are generally UDP based. They do not adjust their throughput in response to, network conditions. They do not easily adapt to changes in delay and throughput e.g. real-time multimedia traffic, CBR, VBR, LOOKUP. The services required by inelastic are: 1. Throughput: A minimum throughput may be required for data transmission. 2. Delay: An upper bound on delay may be required. 3. Packet Loss: An upper bound on packet loss percentage due to congestion may be required. IV BLACK HOLE ATTACKS The black hole attack has a severe impact on the routing protocols which uses sequence number to determine whether the route is up to date or not and select the shortest path consisting of minimum hops. In AODV routing protocol when a source node broadcasts a Route Request (RREQ) message to other nodes rather than a black hole node, then the intermediate nodes will continuously broadcast the RREQ while a black hole node with largest sequence number will directly send a Route Reply (RREP) message to the source node. As per working and design of AODV protocol, it will select the RREP with latest sequence number and shortest route to send the packets. The source node ignores the RREP packet received from other nodes and begins to send the data packets over malicious node. A malicious node takes all the routes towards itself. It does not allow forwarding any packet anywhere. This attack is called a black hole as it swallows all data packets. [5] [6] When the route is established the black hole node will start dropping all the incoming packets which will severely affect the network security and performance. Black hole attacks can be classified into two categories: Internal Black hole attack: In this type of black hole attack a single node from within the network act as an attacker node. It is also known as a Single Black hole attack. External Black hole attack: In this attack multiple nodes collectively act as attacker node. It is a kind of attack which is done with a multiple nodes in a group. 2. Data Loss: They require 100% reliable transmission. 2

3 WORKING OF BLACK- HOLE ATTACKS A B C black-hole attack in MANET using the AODV routing protocol and the analysed its impact by varying the number of malicious nodes in the network. VI SIMULATION AND RESULTS S D Figure 1 Strategy of Black hole attack Fig. 1 shows how the black hole problem arises, here node S wants to send data packets to node G and initiate the route discovery process. So if node C is a malicious node, then it will claim that it has an active route to the specified destination as soon as it receives RREQ packets. It will then send the response to node S before any other node. In this way node S will think that this is the active route and thus the active route discovery is complete. Node S will ignore all other replies and will start seeding data packets to node C. In this way all the data packets will be lost consumed. V RELATED WORK Over recent years, significant work has been conducted to evaluate the performance of adhoc wireless networks under black hole attacks. Sharma and Gupta [9] have analysed the impact of black hole attacks on network performance. The black hole attacks are simulated in Qual net Simulator and packet loss is measured in the network with and without a black hole. The simulation is done on an AODV routing protocol. They have concluded that the network performance in the presence of a black hole is reduced up to 26%. Roopak and Reddy [10] have done a simulation study of network under black hole attack and do compared to the network without attack working on AODV protocol using various performance metrics such as throughput, PDR and End to End delay in three different scenarios and it is concluded that as the number of attackers increases in each scenario the throughput degrades and End to End delay increases. Kumar et al. [11] have analysed the effects of the black hole attack on mobile ad-hoc routing protocols. The effect of a black hole has been analysed on three performance metrics only, i.e., Packet delivery ratio (PDR), Delay and Control Overhead. The impact of the black hole is analysed by using on attacker node. Kaur et al. [11] has measured the impact of black hole attack on different routing protocols in MANETs i.e. AODV, OLSR, ZRP. The impact of a black hole is measured by considering few performance metrics such as PDR, Average Throughput, Average Jitter and and End to End Delay. The performance of all of the three protocols is compared in the presence of attack and is concluded that AODV performs better than other two protocols. Choudhary et al. [12] They have simulated the E F G We have used Network simulator QUALNET 6.1 in our evaluation. In our scenario we have taken 8 nodes and distributed it over 1000*1000 Terrain areas in Qual net 6.1 Simulator using Elastic and inelastic traffic and by applying 101 sec simulation. We have analyzed the impact of the Black hole attack on AODV by varying the no of attackers.simulation has been conducted by varying the number of attackers and performance of the network is measured under the attacks launched. For each application we have conducted 3 simulation scenarios: Scenario1: no node is an attacker. Scenario 2: node C is an attacker node. Scenario 3: node C and F are attacker node. PARAMETERS TABLE I: SIMULATION PARAMETERS VALUE SIMULATOR QUALNET 6.1 SIMULATION TIME DATA PACKET SIZE 101SEC 512BYTE ENVIRONMENT SIZE 1000*1000 NUMBER OF NODES 8 ROUTING PROTOCOL ENERGY MODEL 3 AODV NUMBER OF PACKETS SENT 100 APPLICTAION NUMBER OF ATTACKERS 0-2 MICA MOTES ELASTIC/INELASTIC Figure 1. Impact of black hole on jitter in Elastic

4 Jitter: In Figure1 x-axis represents number of black hole nodes and y-axis represents the value of jitter with is taken for 101 seconds for elastic. The attack on the network the value of jitter for FTP, HTTP and TELNET is 1.19, 1.15 and but as the number of attacks have increased the value of Jitter for FTP, TELNET and HTTP increases, out of which the highest impact is seen on HTTP due to increase in the number of attacks. throughput for FTP, HTTP and TELNET is ,10351 and 8 but as the number of attacks have increased the value of throughput for FTP and HTTP decreases the most, out of which the highest impact is seen on HTTP due to increase in the number of attacks. Figure 4. Impact of black hole on throughput in inelastic Figure 2. Impact of black hole on jitter in inelastic In Figure 2, x-axis represents number of black hole nodes and y-axis represents the value of jitter with is taken for 101 seconds for an inelastic application. The attack on the network the value of jitter for CBR, VBR and LOOK UP is , and but as the number of attacks have increased the value of Jitter for CBR, VBR and LOOK UP increases, out of which the highest impact is seen on CBR due to increase in the number of attacks. In Figure 4, x-axis represents number of black hole nodes and y-axis represents the value of throughput with is taken for 101 seconds for an inelastic application. The attack on the network the value of throughput for CBR, VBR and LOOK UP is 4055, and 1.36 but as the number of attacks have increased the value of throughput for CBR, VBR and LOOK UP decreases, out of which the highest impact is seen on CBR due to increase in the number of attacks. Figure 3. Impact of black hole on throughput in elastic Throughput: In Figure 3, x-axis represents number of black hole nodes and y-axis represents the value of throughput with respect to the number of attacks. The complete scenario is taken for 101 seconds for elastic. The black hole nodes vary from 0-2 i.e. Figure 5. Impact of black hole on delay in elastic Delay: In Figure5, x-axis represents number of black hole nodes and y-axis represents the value of delay with is taken for 101 seconds for elastic. The attack on the network the value of delay for FTP, HTTP and TELNET is 1.478, 4.4 and but as the number of attacks have increased the value of delay for FTP and HTTP increases the most, out of which the when there is no attack on the network the value of 4

5 highest impact is seen on HTTP due to increase in the number of attacks. Figure6. Impact of black hole on delay in inelastic In Figure 6, x-axis represents number of black hole nodes and y-axis represents the value of delay with respect to number of attacks. The complete scenario is taken for 101 seconds for inelastic. The black hole nodes are varied from 0-2 i.e. when there is no attack on the network the value of jitter for CBR, VBR and LOOK UP is , and but as the number of attacks have increased the value of Jitter for CBR, VBR and LOOK UP increases, out of which the highest impact is seen on CBR due to increase in the number of attacks. Figure8. Impact of black hole on number of packets dropped in inelastic In Figure 8, x-axis represents number of black hole nodes and y-axis represents the number of packets dropped with respect to number of attacks. The complete scenario is taken for 101 seconds for inelastic. The black hole nodes are varied from 0-2 i.e. when there is no attack on the network the number of packets dropped for CBR, VBR and LOOK UP is 0, 1, 33 but as the number of attacks are increased the number of dropped packets increases the most for VBR as the in the number of attacks increases. Figure7. Impact of black hole on number of packets dropped in elastic Packets Dropped: In Figure 7, x-axis represents number of black hole nodes and y-axis represents the value of number of packets dropped with respect to number of attacks. The complete scenario is taken for 101 seconds for elastic. The black hole nodes are varied from 0-2 i.e. when there is no attack on the network the number of packets dropped for FTP, HTTP and TELNET are 3, 1, 1but as the number of attacks are increased the number of dropped packets increases for FTP, HTTP and TELNET but the highest number of packets dropped in case of HTTP. Figure9. Impact of black hole on PDR in elastic PDR: In Figure9, x-axis represents number of black hole nodes and y-axis represents the value of the PDR with respect to number of attacks. The complete scenario is taken for 101 seconds for elastic. The black hole nodes are varied from 0-2 i.e. when there is no attack on the network the value of PDR for FTP, HTTP and TELNET is , and but as the number of attacks are increased the value of PDR decreases the most for FTP and HTTP. Figure10. Impact of black hole on PDR in inelastic 5

6 In Figure 10, x-axis represents number of black hole nodes and y-axis represents the value of PDR with respect to number of attacks. The complete scenario is taken for 101 seconds for inelastic. The black hole nodes are varied from 0-2 i.e. when there is no attack on the network the value of PDR for CBR, VBR and LOOK UP is 0.97, and but as the number of attacks are increased the value of PDR decreases the most for CBR and VBR. VII CONCLUSION AND FUTURE SCOPE The impact of black holes is severe in case of inelastic as compared to elastic. In case of inelastic application the performance of CBR is highly affected due to the attack. In case of elastic application the performance of HTTP decreases the most as the no of attacker increases. Black hole attacks are needed to be analyzed on other existing MANETs routing protocols such as DSDV, ZRP, DSR, etc. Also attacks other than black hole such as Wormhole, passive and active attacks shall be considered. They can be classified on the basis of how much they affect the performance of an ad-hoc network. The early detection of Black hole attacks as well as the exclusion policy for such actions shall be carried out for advance research. REFERENCES [1] Boundpadith Kanhavong, Hidehisa Nakayama, A survey of Routing Attacks in Mobile Adhoc Networks, Jamalipour, University of Sydney. [2] M. Abolhasan, T. Wysocki, E. Dutkiewicz, A Review of Routing Protocols, Mobile Ad-Hoc Networks, Telecommunication and Information Research Insti University of Wollongong, Australia, June, 2003 [3] B.Revathi, D.Geetha, A Survey of Cooperative Black and Gray hole Attack in MANET, International Journal of Computer Science and Management Research, 2012 [4] H. A. Esmaili, M. R. Khalili Shoja, Hossein gharaee, Performance Analysis of AODV under black hole attacks using OPNET simulator, World of Computer Science and Information Technology Journal (WCSIT) Vol. 1, No. 2, 49-52, [5] Himani Yadav, Rakesh Kumar, A review of black hole attacks in MANETS, International Journal of Engineering Research and Applications, May-Jun [6] Abhishek Choudhary, Kunal, Performance Evaluation of AODV under Black Hole Attack, International Journal of Emerging Technology and Advanced Engineering. [7] Vikas Solomon Abel, Survey of Attacks on Mobile Adhoc Wireless Networks, International Journal on Computer Science and Engineering (IJCSE). [8] [9] Sheenu Sharma, Roopam Gupta, Simulation Study of Black hole attack under Mobile Adhoc Networks, Journal of Engineering Science and Technology Vol. 4, No. 2 (2009) [10] Monika Roopak, Dr. Bvr Reddy, Performance Analysis of Aodv Protocol under Black Hole Attack, International Journal of Scientific & Engineering Research Volume 2, Issue 8,August [11] Jaspal Kumar, M. Kulkarni, Daya Gupta, Effect of Black Hole Attack on MANET Routing Protocols, I. J. Computer Network and Information Security, 2013, 5, Published Online April 2013 in MECS. [12] Harjeet Kaur, Manju Bala, Varsha Sahni, Study of Black Hole Attack in MANET, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering Vol. 2, Issue 7, July [13] Abhishek Choudhary, Kunal, Performance Evaluation of AODV under Black Hole Attack, International Journal of Emerging Technology and Advanced Engineering.. [14] Rutvij H. Jhaveri, Ashish D. Patel, MANET Routing Protocols and Worm hole Attack against AODV, International Journal of Computer Science and Network security,

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