This paper describes the different types of attacks that are very common i.e. the Distributed Denial of Service attack, the Blackhole attack and the Wormhole attack, also provide the mechanism to detect these attacks using the different techniques and the relative comparison between these three attacks.
ISSN:2249-5789 Krutika K Chhajed et al , International Journal of Computer Science & Communication Networks,Vol 5(3),184-191 Distributed Security System for Mobile Ad-Hoc Computer Networks Ms.Krutika K Chhajed Department of Computer Science & Engg PRMIT & R, Badnera Abstract— Ad-hoc wireless networks are increasing in popularity, due to the spread of laptops, sensor devices, PDAs and other mobile electronic devices These devices will eventually communicate with each other and hence there is a need of security in MANETS.This paper describes the different types of attacks that are very common i.e the Distributed Denial of Service attack, the Blackhole attack and the Wormhole attack, also provide the mechanism to detect these attacks using the different techniques and the relative comparison between these three attacks It provides a comparison of some of the common parameters on the different nodes in these different types of attack scenario So that a novel and optimum solution can be provided, this can secure the nodes from different types of attacks Keyword: MANET, DDoS attack, Blackhole, Wormhole attack INTRODUCTION Ad-hoc wireless networks are increasing in popularity, due to the spread of laptops, sensor devices, PDAs and other mobile electronic devices These devices will eventually need to communicate with each other However there is a need to implement a secure ad hoc network that might be used in emergency services, disaster assistance, and military applications The security includes controls to limit access to the network, in order to protect it from intruders or unwanted bystanders Mobile Ad hoc Networks are the networks formed for a particular purpose These networks assume that an end to end path between the nodes exists They are often created on-the-fly and for one-time or temporary use They find their use in special applications like military, disaster relief etc that are in a need of forming a new infrastructure less network with all pre-existing infrastructure being destroyed [2] The basic working of MANETS is such that every node is independently working and only keeping the routing information with respect to other node, it becomes difficult for the node to keep track of each and every node entering and leaving the MANET and hence it becomes very easy for an unintended node to enter into the MANET and attack the network to disrupt the normal working Implementing security in MANET is a challenging task Because here node itself will be acting as a router node So identifying neighbor node as a legitimate node or malicious node is a difficult thing in MANET [3]Thus security of the data is the most important aspect to be handled when dealing with MANETS A Mobile Ad hoc Network (MANET) is a collection of mobile node connected through wireless links Dr M S Ali Principal, PRMCEAM, Badnera [3].The MANETS are different from the traditional infrastructure based networks in the way that there are nodes which are mobile And hence the challenges in such networks are different from traditional infrastructure based networks Security Challenges in MANETS: a) Dynamic Topology: the nodes are moving and may leave or join the network dynamically Establishing the trust among the network nodes is difficult b) Battery constraints: the nodes are mobile and work on battery so power consumption must be less c) Lack of Central authority: In MANETS there will be no central authority So to implement security is a challenging task d) Insecure Environment: the nodes are continuously moving so it is difficult to find out the malicious nodes which can attack and steal the data [1] In Ad hoc networks every node act as the sender receiver and also as a router because it lacks the central authority The routing protocols are needed for transmitting the data from source to destination using multiple hops There are two basic suggested approaches for routing in MANETS These are Topology Based Routing and Position Based Routing Topology-based routing protocols use the information about the links that exist in the network to perform packet forwarding They can be further divided into proactive, reactive, and hybrid approach Position-based routing algorithms eliminate some of the limitations of topology-based routing by using additional information They require that information about the physical position of the participating nodes be available Commonly, each node determines its own position through the use of GPS or some other type of positioning service A location service is used by the sender of a packet to determine the position of the destination and to include it in the packet’s destination address Attacks in MANETS Table1 gives a few examples of attacks at each layer Some attacks could occur in any layer of the network protocol stack, e.g jamming at physical layer, hello flood at network layer, and SYN flood at transport layer are all DoS attacks Table 1: Attacks occurring at different layers in protocol stack Layer Attacks Application Layer Transport Layer Network Layer data corruption, viruses and worms TCP/UDP SYN flood hello flood, blackhole Data Link Layer monitoring, traffic analysis Physical Layer eavesdropping, active interference 184 ISSN:2249-5789 Krutika K Chhajed et al , International Journal of Computer Science & Communication Networks,Vol 5(3),184-191 The network layer attack on ad hoc networks can be broadly classified into two categories one based on source of attacks [17] i.e External and internal attacks and the other based on the behavior of attack i.e active and Passive attacks In external attack, attacker from outside the network tries to get the access to the current network and once it becomes the part of the network, interrupts the ongoing transmission and performance External attacker can flood network bogus packets in the network to cause congestion in the network They can be prevented by implementing the firewalls In Internal attack, the attacker node is already the part of the network, and also contributes in normal network activities, but after some time, it starts with the malicious behaviour It is more difficult to detect as compare to the external attacks DPRAODV checks to find whether the RREP_Seq_No is higher than the threshold value M Umaparvathi, and D K Varughese [24] proposes two tiers secure AODV (TTSAODV) routing protocol which is an extension over AODV protocol In tier security, the previous and the next hop of any intermediate node exchanges the verification messages to verify that the next hop of the intermediate hop is also having the fresh path to the destination.Similarly for detecting collaborative black hole attack, tier protocol is used.Jitendra kumar Rout et al [25] proposed a Secure Fault- Tolerant Paradigm (SFTP) which checks the Blackhole attack in the network The Wormhole Attack was introduced in [26], [27], [28] In this an attacker, or potentially multiple colluding attackers, surreptitiously relay packets between distant locations This can give a node the impression that it is the neighbor of a node that is far away Y C Hu et al [26] introduced Packet Leashes method in which two types of methods have been considered: The Geographic leashes and the temporal leashes In Geographic leashes, node location information is used to bind the distance a packet can traverse Lazos L, et al [29] proposed a graph theoretic model to characterize the wormhole attack and ascertain the necessary and sufficient conditions for any candidate solution to prevent wormholes They used a Local Broadcast Key (LBK) based method to set up a secure ad-hoc network against wormhole attacks J Eriksson et al [30] proposed a practical countermeasure to the wormhole attack that presented as an extension to the IEEE 802.11 MAC layer RELATED WORK Wei-Shen Lai et al [11] have proposed a scheme to monitor the traffic pattern in order to alleviate distributed denial of service attacks This mechanism adopts the bandwidth allocation policy to assign normal users to higher priority queue and the suspected attackers to the lower priority queue S.A.Arunmozhi, Y.Venkataramani [12] discussed the mechanism of DDoS attack and proposed the defense scheme to detect the DDoS attacks In this scheme the proposed defense mechanism uses the MAC layer information to detect the attackers Rizwan Khan, A K Vatsa [14] proposed a clustering based prevention technique for the DDos attacks Niresh Sharma, Rajdeep Singh et al [15] proposed the secure IDS to detect this kind of attack and block it The algorithm was proposed which uses the Anomaly based Intrusion detection system which uses different intrusion detection parameters such as packet reception rate, inter arrival time V.Priyadharshini and Dr.K.Kuppusamy [18] proposed a new Cracking algorithm for detection of DDOS attack The term “Blackhole” suggests a node which absorbs all information passing through it by not forwarding it to the destination node As a result of the dropped packets, the amount of retransmission needed increases leading to congestion Several schemes have been proposed for detecting preventing the black hole attack some of the methods can be stated as follows H Deng, W Li and D P Agrawal, [19] have proposed a solution to cope with the black hole attack in AODV First, they suggest disabling the ability of an intermediate node to send a RREP and allow only the final destination to that T hey have proposed another solution which requires that the intermediate node adds its next hop’s information to the RREP packet before sending it B Sun et al [20] proposed a new scheme to ascertain the safety of the established path to secure AODV H Miranda and L Rodrigues [21] proposed another scheme based on reputation system so called Friend and Foes This scheme aims to prevent the selfish nodes from disrupting the network operations by refusing to participate correctly to the forwarding process E Gerhards-Padilla et al [22] proposed a TOGBAD approach to defend against colluding black hole attack in tactical MANETs, in which a successful attack can lead to human life loss Raj PN et.al [23] discuss a protocol viz DPRAODV (Dynamic, Prevention and Reactive AODV) to counter the Black hole attacks Unlike normal AODV, The following table summarizes the different techniques discussed above Table 2: Summary of different techniques for Detection and prevention of attacks in MANETS Sr Attack Detection/ Prevention Wei Shen Lai DDoS Detection S.A.Arun mozhi DDoS Detection Status values from MAC Layer Minda Xiang DDoS Mitigation after attack Using Load Protection Node Rizwan Khan DDoS Prevention Clustering based Niresh Sharma DDoS Detection Laxmi Bala DDoS Detection & Prevention Quality Based Bottom Up Detection Dr.K.Ku ppusamy DDoS Detection New Cracking algorithm No Author Method Priority Queue based schemes Anomaly Based Intrusion detection system 185 ISSN:2249-5789 Krutika K Chhajed et al , International Journal of Computer Science & Communication Networks,Vol 5(3),184-191 H Den Blackh ole Mitigating after attack Allow final destination to send RREP B Sun Blackh ole Mitigate after attack Cryptography based reaction mechanism 10 H Miranda Blackh ole Prevention Reputation based Friends and Foes 11 E.Padill a Blackh ole Detection Topology graph based anomaly detection 12 Raj PN Blackh ole Detection and prevention DPRAODV approach 13 M Umaparv athi Blackh ole Prevention Two tier Secure AODV approach 14 Jitendra kumar Rout et al 15 Y C Hu et al 16 17 Lazos L, et al J Eriksson et al 18 ShangMing Jen et al 19 Ritesh Mahesh wari, 20 Dr A Francis Devaraj Secure Fault Tolerant Paradigm approach Blackh ole Detection Wormh ole Detection Wormh ole Prevention Wormh ole Prevention Wormh ole Detection Wormh ole Detection Connectivity Graph information Wormh ole Detection and Prevention Multilayer detection approach Packet Leashes temporal and Geographic Graph Theoretic approach Truelink, extension to the 802.11 MAC layer Hop count Analysis scheme using MHA algorithm Fig : Basic block diagram of the proposed system Each of the three modules first creates the MANET environment and then simulates the attack in that environment After attack simulation the system apply the technique for detection and detects the attack and register the values of different parameters of the node in the trace files or the awk files which can be then used for generation of graphs and studying the behavior of the system The basic steps of each of the module can be shown a in the fig 3.2 below PROPOSED SYSTEM The proposed system consists of three independent modules each of which deals with one of the type of attack the DDoS, Blackhole and the Wormhole attack Each of these modules works independently and creates different trace files which can then be used to generate comparison graphs The basic work of the system can be shown in Fig.1 below: Fig 2: Basic flow of each of the attack detection module a) Design of the module to illustrate the DDoS attack: The design of the module required for the illustration of the DDoS attack consists of following basic steps: 186 ISSN:2249-5789 Krutika K Chhajed et al , International Journal of Computer Science & Communication Networks,Vol 5(3),184-191 Create number of nodes to form a network Setup the links between these nodes Setup the MANET environment for these nodes Create files to trace the simulation as well as monitor queue that stores packet Start the simulation and note the values in the trace files Read the trace files in different awk files for different nodes Generate graphs based on the data at different node before attack and after attack b) Design of the module for illustration of Black hole attack: For the illustration of the black hole attack the algorithm can be given as follows: Create the patch file for setting the AODV protocol environment and patch it to the current network simulator environment Create the nodes and assign the properties to these nodes relevant to the MANET environment Set one node as the blackhole node Simulate the blackhole attack in the simulator using the tcl file and record the output of the simulation in the trace file Read the trace file to check the effect of blackhole attack on the ad hoc network c) Design of the module for illustration and detection of Worm hole attack: The wormhole attack is simulated in the MANET environment as follows: Create the nodes and set the MANET environment Create the node environment Start the simulation and during the simulation run the CPP code for the detection of the wormhole attack using unit disk graph method Note the contents in the trace files to check the effect of wormhole attack on the network i ii iii Node u determines the set of common k-hop neighbors with v from their k-hop neighbor lists This is Ck (u, v) = Nk (u) ∩ Nk (v) Node u determines the maximal independent set of the sub-graph on vertices Ck (u, v) by using a greedy approach If the maximal independent set size is equal or larger than fk , node u declares the presence of a wormhole SYSTEM IMPLEMENTATION & TESTING 1) Setting Environment To implement the proposed smoothly, we need to have one of the various versions of LINUX operating system which can be either Red Hat or Fedora or Ubuntu and we need to install the Network Simulator version 2.2 or onwards software tool to support complete functionality of the product In addition to NS-2, we developed a set of tools, mainly Bash scripts and AWK filters, to post-process the output trace files generated by the simulator Some scripts were also written to help with the configuration and running of the multiple experiments we have carried out In order to evaluate the performance, we set up multiple experiments In every experiment, we run a NS-2 simulation for each type of attack and different scenarios The exact environment and parameters will be discussed System Execution Details The system executes by simulating different attacks individually and the tracing the values generated from these simulations The algorithm used for the detection of the wormhole attack is the Unit Disk Graph algorithm which uses the connectivity graph Information for finding out the forbidden nodes in the graph and thus detecting that the attack has occurred The Unit Disk Graph algorithm can be stated as follows: In UDG each node is modeled as a disk of unit radius in the plane Each node is a neighbor of all nodes located within its disk The basic idea in our detection algorithm is to look for graph substructures that not allow a unit disk graph embedding, thus cannot be present in a legal connectivity graph Inside a fixed region, one cannot pack too many nodes without having edges in between The forbidden substructures we look for are actually those that violate this packing argument Fig 3: The network simulation created for the DDoS attack The first screenshot shows the simulation of the network for the with total 16 nodes distributed in the diferent groups The nodes and are the nodes which takes the data coming from different distributed nodes for the other part of the network ALGORITHM: Find the forbidden parameter Fk based on value of k selected Each node u determines its 2k-hop neighbor list, N2k (u), and executes the following steps for each non neighboring node v in N2k (u): 187 ISSN:2249-5789 Krutika K Chhajed et al , International Journal of Computer Science & Communication Networks,Vol 5(3),184-191 Fig.4: Service denied at node 16 due to dropping of legitimate packets Fig shows the actual DDoS attack scenario where the actual legitimate packets are dropped at node 15 and are not sent to the destination node due the congestion in the link and queue overflow some of the packet may be sent further to the actual destinations Fig 7: simulation of Wormhole Attack Fig shows the simulation of the wormhole attack Here the unit disk graph method is used to detect the forbidden nodes Fig 8: Result of wormhole attack detection Fig 5: The graph showing the total number of packets received After this the Blackhole attack is simulated Fig shows the total no of packet received by the destination node From the graph it is clear that initially the received packet number is zero but when the attacker nodes starts attacking the number of packets starts increasing and after some time it continues to the maximum capacity Fig simulation of Blackhole Attack Fig.6: The graph showing the entropy of node RESULT ANALYSIS Fig shows the entropy of node In this the red line indicate the ratio of the normal packets received to the total packets received at node and the green line indicates the ratio of the attack packets received to the total packets received at a node After the simulation of the attacks the trace files generated after the simulation of each of the attack is considered and the values of different parameters are calculated as follows: After the DDoS attack scenario the Wormhole attack is simulated with the different environment The different parameter values obtained for the Blackhole attack in attack condition can be given in the table 4.1 as follows: 188 ISSN:2249-5789 Krutika K Chhajed et al , International Journal of Computer Science & Communication Networks,Vol 5(3),184-191 Table Results obtained for Blackhole attack Parameter Value Average energy 0.001246 Average end to end delay 0.418301 PDR 0.040323 The different values obtained for throughput can be given as Table Throughput of blackhole attack at different conditions Throughput Before attack During Attack 89.96538 7.3096 The different parameter values obtained for the DDoS attack can be given in the table 4.3 as follows: Fig 10.Comparative graph for packet delay in each of the attack From the above results it is clear that the throughput of the network decreases when the attack occurs Also the attack decreases the throughput to a large extent The average delay and the Packet delivery ratio also decreases when there is an attack in the system Table Results obtained for DDoS attack Parameter Average Energy Average packet sent Value 0.0055 14.8425 CONCLUSION The different parameter values obtained for the Wormhole attack can be given in the table 4.4 as follows: Table Results obtained for Wormhole attack Parameter Average End to end delay Value 2.63 0.014 The values of the packet delay for each of the attacks can be given as follows: Table Comparison table for the packet delay of the network Packet delay attcker DDoS Blackhole Wormhole 0.4138 0.4132 0.10056 0.42533 0.4192 0.12833 0.43133 0.4212 0.28 The comparative graph can be given between the three attacks for the above table as below: From these discussions we can say that even if there are so many techniques for detection and prevention of different types of attacks, no methodology provides the complete protection from the attacks and also the each of these methodologies has some or other type of loophole in it Thus the system can detect and analyze the different attacks and 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Technology in Computer Science, Vol.3, issue 1, pp 274-279, Feb 2014 [4] Alex Hinds, Michael Ngulube, Shaoying Zhu and Hussain-Al-Aqrabi, “A Review of Routing Protocols for Mobile Ad- hoc Networks