Algorithm for Detection of Sinkhole Attacks in Wireless Sensor Network

Home , Ant colony

International Journal of Mechanical Engineering and Technology (IJMET) Volume 8, Issue 8, August 2017, pp. 193–202, Article ID: IJMET_08_08_022 Available online at http://iaeme.com/Home/issue/IJMET?Volume=8&Issue=8 ISSN Print: 0976-6340 and ISSN Online: 0976-6359

AN ENRICHED ARTIFICIAL BEE COLONY (EABC) ALGORITHM FOR DETECTION OF SINKHOLE ATTACKS IN WIRELESS SENSOR NETWORK

R.S. Raghav, Sujatha Pothula, Dhavachelvan Ponnurangam Department of CSE, Pondicherry University, Pondicherry, India

ABSTRACT In present world Wireless Sensor Networks plays a major role for monitoring the movement of autonomous nodes in an environment. It also has the ability to provide low cost sensor nodes with high availability in the various types of environment. The WSN are mostly adhoc in nature, where they don’t have any fixed topology to be followed. The WSN comprises of sensor nodes used for collecting data and monitoring the both static and dynamic environment. The structured and unstructured are the two main classification of sensor network. In unstructured wireless network the sensor nodes are closely populated and they are deployed dynamically in the environment. The characteristics of WSN as some of the vulnerabilities such as dynamic topology limited bandwidth and limited battery power. This work restrains its focus on how to defend against a particularly dangerous form of at attack, which is created by the Sinkhole node. The Sinkhole is also portrait as a service attack; it prevents base station from receiving or gathering complete and accurate information about the nodes. In this attack, a node tries to drag the data to it from his all neighboring node. In this paper we are going to deploy an Enriched Artificial Bee Colony (EABC) algorithm to observe the sinkhole attacked node in the network. It will be intimated to the base station and the changes in the position of the estimated node should be monitored continuously. To develop an enriched Swarm Intelligence algorithm based on Artificial Bee Colony optimizer, which gives global exploration of multiple paths to transmit data from sensor to sink nodes at the absence of sinkhole nodes. Key words: Wireless Sensor Network (WSN), Enriched Artificial Bee Colony (EABC), Sinkhole Attacks, Security. Cite this Article: R.S. Raghav, Sujatha Pothula, Dhavachelvan Ponnurangam, An Enriched Artificial Bee Colony (EABC) Algorithm for Detection of Sinkhole Attacks in Wireless Sensor Network, International Journal of Mechanical Engineering and Technology, 8(8), 2017, pp. 193–202. http://iaeme.com/Home/issue/IJMET?Volume=8&Issue=8

http://iaeme.com/Home/journal/IJMET 193 [email protected] R.S. Raghav, Sujatha Pothula, Dhavachelvan Ponnurangam

1. INTRODUCTION Wireless Sensor Networks (WSN) plays a vital role in recent years; particularly they are used for developing smart sensors [1][2][3][4]. These smart sensor are geographically distributed, in order to monitor the environment. The routing process in wireless network is carried by multihop and this process is done by gathering information from various sensor nodes [5][6][7][8][9]. Then it is forwarded to the base station with the help of multihop routing. The node placement was done without following any structure and there is a chance of placing the nodes in a remote area[10][11][12][13][14][15]. Thus it require a proper protocol and algorithm for deploying the nodes in wireless environment and these nodes should be protected from the various types of attacks in the wireless network. The sensor nodes can be managed in the terms of the transmission medium[16][17][18][19][20]. The network can become vulnerable due to the security attacks in the network layer and some of the harmful are sinkhole attack, selective forwarding, Sybil attack spoofed or replayed routing and Wormhole attack [21][22][23][24][25]. N.K. Sreelaja, G.A. Vijayalakshmi Pai, 2014 applies nature inspired computing algorithm an situated within the context of agent based models, which impersonate the behavior of ants to reveal sinkhole attacks in wireless sensor networks [1]. An Ant Colony Optimization Attack Detection (ACO-AD) algorithm is proposed to find the presence of sinkhole node ids. An alert message is generated once the detection of sinkhole attack takes place in the network. The network voting method is carried once the intruder in a network. An Ant Colony Optimization Boolean Expression Evolver Sign Generation (ABXES) algorithm is proposed and the suspect list is generated and the key distribution to the alerted nodes in the group for is carried by signing the suspect list to agree on the intruder. C.H. Ngai, 2007 [2] proposes an algorithm for identifying the illegitimate node in a sinkhole attack. The algorithm has the ability to detect the list of suspected nodes, with the help of monitoring data consistency. It helps to find the intruder placed in the list, by analyzing the network flow information. The algorithm consists of two steps: The data consistency checks the suspect nodes located in the list by analyzing the network flow information. The algorithm provides complete protection with multiple malicious nodes that cooperatively hide the real intruder. The performance of the proposed algorithm is evaluated by both numerical analysis and simulations, by knowing the effectiveness and accuracy of the algorithm. The communication and computation overheads are less for wireless sensor networks. Nidal Nasser,2007 [3] discuss about an important issue about the architecture of wireless sensor network. The energy limitations are represented by the routing protocol which uses limited resource presented by WSN. The important factor required for researchers is to give more security to the application as possible. The author proposed routing protocols by understanding the concept of increasing lifetime of network and security issues is also addressed consuming much power. SEEM: Secure and Energy-Efficient multipath Routing protocol for communicating between two nodes which increase the lifetime of the network. On the other hand, SEEM provides immune to some specific attacks and it has the ability to grab the behavior of all traffic through the malicious nodes, by creating an attractive route to the destination. H.Shafiei, A. Khonsari, 2014 [4] proposes two main approaches to identify these kinds of attack staged in WSNs. A geostatistical hazard model is used as a centralized approach for identifying suspicious nodes in the network. The exploration of neighborhood in the network is done for finding malicious node in distribution environment [26][27][28][29][30]. An analytical model is used for capturing communication carried between various parameters in the proposed detection methods [31][32][33][34][35]. In this paper author discuss about the two main approaches for finding the sinkholes in the network. The concept discussed here is the depletion of energy in the sinkhole nodes is quicker than

http://iaeme.com/Home/journal/IJMET 194 [email protected] An Enriched Artificial Bee Colony (EABC) Algorithm for Detection of Sinkhole Attacks in Wireless Sensor Network remaining nodes. The routes to the base-station are generated and the communication is carried through sinkhole which is more attractive. In first approach, a geo-statistical method is used to sample the residual energy of every sensing region. The statistical estimator is sued for finding the possibility of occurrence of the sinkhole in each area. Based on the value of the estimator, the base-station orders all of the nodes to leave the suspicious region in their routing. The distributed monitoring method is second approach for finding regions with lower average residual energy level. A light weight mitigation method is used for sinkhole elimination. A mitigation scheme is discussed for preventing the traffic flow toward sinkholes .This strategy helps to eliminate the threat of the sinkholes. Fessant,2012 [5] tree based routing is used for discussing about the impact of selective forwarding attacks in wireless sensor networks (WSNs). The second method is used for investigating cryptography-based strategies to minimize degradation of network caused by sinkhole attacks. The main theme of research is to know WSN protocols, which construct a fixed routing topology which is affected by malicious attacks. Second, considering networks deployed in a complex geographical region, by constructing immune against such attacks. The simulation study on the impact of malicious attacks is completely based on a diverse set of parameters such as network scale, position of malicious nodes. Based on the evaluation, the proposed a metric for describing the impact which describes about the design and evaluation of two simple and resilient topology-based reconfiguration protocols.

3. PROPOSED SYSTEM 3.1. Problem Statement In a sensor network, a base station (BS) collects information from the nodes geographically distributed environment. The sensor nodes continuously collect and forward the sensed data to the base station in a multihop routing. To sinkhole attacks the many-to-one communication pattern is indefensible and this type of attack is carried out in network layer. The attacked node tries fetching traffic information to prevent base station from receiving a complete sensing data from malicious nodes. It also presents a novel algorithm for identifying the intruder in a sinkhole attack. The algorithm consists of two steps: The suspected nodes monitors' data consistency, by finding malicious node in the list. This process is done by analyzing the network flow information. The algorithm gives protection to deal with variety of malicious nodes especially from the hidden intruder. The performance of the proposed algorithm is evaluated by numerical analysis and simulations. The result describes about the efficiency and accuracy of the algorithm. The Clustering of nodes to identify the sinkhole attacked node in the large network by certain criteria will be a tedious process and also the estimation of sinkhole nodes is not much efficient because many nodes in the network can be suspected and it can’t be able to narrow down to detect a particular node. So it is highly time consuming and energy consumption process. It is stated to make the huge set of nodes into groups based on some measures but there is no word about the way of clustering. The estimation of sinkhole nodes is not much efficient since a random threshold value is stated which points many nodes can be suspected and it can’t be able to narrow down the idea to detect a particular node. It is a time consuming process. Another issue in the existing system is after the detection of the sinkhole attacked node from the network, the existing path using the node will be failed so the transmission using that node will be disabled and the alternative path for the transmission is not available so the entire network efficiency will also be less.

3.2. Enriched Artificial Bee Colony (EABC) algorithm The focus of the proposed system is to effectively identify the sinkhole attack in the network. Once the nodes are identified with their position, the monitoring of the node will take place

http://iaeme.com/Home/journal/IJMET 195 [email protected] R.S. Raghav, Sujatha Pothula, Dhavachelvan Ponnurangam periodically for true topological information. This strategy will help to enhance the data consistency in the large network and it also periodic monitoring of the node position makes the WSN to work in an efficient way. The proposed system, Enriched Artificial Bee Colony (EABC) algorithm is designed to detect the sinkhole attacked node from the network and it monitors the malicious node continuously by updating their position. This type of methodology is done, in order to find the true sink node because the illegitimate nodes position will be changing in irregular interval of time within the network. First, the Artificial Bee Colony (EABC) algorithm is initialized which incorporates bee's behavior with the position of the nodes in the network. It estimates the network load for each and every node and the searching of sinkhole node which creates an attack will be found. Once the attack node was removed in the network, the multiple paths for each and every node in the network will be formed in order to transfer of messages from the source to the destination. The alternate path selection can be done by using ABC at the initial stage. After the detection of the attack from the network, the routing table chooses the path which is next optimal and efficient. EABC carries an optimization based search procedure for each individuals and the placement are dynamic by the artificial bees with respective time. The bee’s goal is to find the places of targeted node with the highest traffic in the network. The search process starts by the employed bees. The ABC algorithm consists of the following steps in it. For all employed bees the initial sources are produced. Repeat the following items; Each employee bee moves to a source in her memory by knowing a neighbor source, where the computing amount of traffic and returns back the information regarding the nodes to the base station. Each onlooker watches the message send by the employed bees and selection of sources is completely depend on the traffic and then it moves to that source. The traffic density is evaluated after choosing a neighbor around network. The food sources are abandoned and they are replaced with the new sources identified by scouts. The best source identified so far is registered. Until (requirements are met). The above procedure explains the involvement of ABC in a set of sensor nodes in WSN. The following phases are included in finding the paths and estimation of Network load using the fitness value of the nodes.

4. EXPERIMENTATION AND RESULT ANALYSIS 4.1. Experimental Design In order to carry the performance evaluations of Artificial Bee Colony algorithm, it was implemented as an evolutionary algorithm in Matlab. This presented several challenges in detecting the sinkhole attack from the Wireless Sensor Network. It uses the network traffic/ load to detect the sinkhole from the network. Here, the experimental design of the wireless sensor network with the artificial bee colony algorithm to detect sinkhole attack contains the following phases.

4.2. Experimental Phases The Simulation of WSN takes place by creating an environment with deploying the nodes. The scope of the first phase describes about the network initialization and introducing of sensor nodes, the fixed position of base station in the network. The hello messages are broadcasted to the nodes present in the network. The HELLO message contains the location of base Station and Hop Count. The hop count is a display the distance of the node to the base station. Once a node receives the HELLO message, the hop count will be saved in its memory and then adding of the hop count by 1. If so, it checks if the hop count of the received message is lesser compared to own message and replaces the message’s hop count with new hop count. By understanding the hop count of the received message and the removal of message are done by checking whether the hop count is larger or equal to its own message.

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4.2.1. LEACH The random placement of nodes in network and it also describes about how LEACH is used to find the sinkhole node in the WSN, Even though some random placement of node is consider as the proper placement. Observation 1: The random placement of node consumes more amount of energy and there is very less amount of energy is saved which is not very effective in WSN. Observation 2: The Packet loss is high if the placement of node is not good, so we need to find a proper or optimal placement for deploying node and to find a sinkhole node, which is not quickly done by these techniques.

4.2.2. PSO The random placement of nodes in network and it also describes about how PSO is used to find the sinkhole node in the WSN, Even though some random placement of node is known as the proper placement. Observation 3: The optimal placement of node consumes less amount of energy and there is when it is compared with LEACH, but it lacks in finding the sinkhole node, which consumes more amount of energy is saved which is not very effective in WSN. Observation 4: The Packet loss is comparatively low than previous technique, because PSO can find optimal path for message communication. But the compromise node could not find immediately.

4.2. 3. EABC Observation 5: The second phase describes about the employee Region: Here the fitness Calculation and Packet Routing is done by the Artificial Bee Colony Algorithm for calculating the fitness of the nodes and selection of the fittest node. As per number of nodes occur in the network, the generation of employee bees to that network should also be same. The employee bee calculated the distance between the nodes and the base station. The fitness value is generated to select the shortest path between the nodes. The following design shows the shortest distance between the source and destination node. Observation 6: The onlooker bee region consists of the following steps to be performed after defining the network load/traffic for each node in the WSN. Estimation of Eminent Network Load From the calculated network load of each node the highest network load node is chosen by the onlooker bee based upon the probability and compared with the threshold value. The network load nodes are arranged based on the diminishing factor. After the selection of network node, the packet delivery ratio, throughput and energy consumption of the node compared with its threshold value. If the node is not in the desirable range then it is considered as the sinkhole attack node. Thus the sinkhole attack from the network is identified. Observation 7: In the scout region, the employee bees works on the nodes will change as scout bees if the nodes are abandoned. Then the scout bees will take charge of finding the nodes with high network load in WSN by using the random value selection from the network. The network initialization is made with the introduction of sensor nodes and the fixed position of base station in the network. The hello messages are broadcasted to the nodes present in the network and it holds the location information of base Station and Hop Count. The hello messages are broadcasted to the nodes present in the network. The HELLO message contains the location of base Station and Hop Count. The hop count is a display the distance of the node to the base station. Once a node receives the HELLO message, the hop count will be saved in its memory and then adding of the hop count by 1. If so, it checks if the hop count of

http://iaeme.com/Home/journal/IJMET 197 [email protected] R.S. Raghav, Sujatha Pothula, Dhavachelvan Ponnurangam the received message is lesser compared to own message and replaces the message’s hop count with new hop count. By understanding the hop count of the received message and the removal of message is done by checking whether the hop count is larger or equal to its own message. In this phase Evaluation of Nodes Using ABC is carried. The network load estimation using the employee bees is done by the sensor node position and energy level present in it. The calculation of the packet routing phase using the fitness value and the network load for each and every node present in the WSN is identified by using the total energy consumption of a node for transmission, receiving, forwarding and idle. In order to compare the results of different algorithms, standard PSO, LEACH and EABC are used to solve the energy consumption of a sinkhole node problem. The ABC algorithm named as Enriched artificial bee colony (EABC) is proposed to handle these issues, the parameters represents in the table1 explains about the different numerical values with multiple network loads using LEACH. The performances factors like packet delivery ratio and energy consumption by sinkhole node were displayed. The results are compared with other algorithms like LEACH and PSO. The fig 3 describes about the average energy consumed of a node in the network and it is calculated depends upon the network load. The first one is LEACH which is known as energy efficient in WSN, even though they are very good in saving energy but the lacks in some criteria. The placement of node is not deployed properly, where it can't able to find the optimal placement for node. This consumes some energy which is not good in WSN and the energy consumed by SH is high. The energy consumption is NIL when sinkhole nodes are absent in a network. The second technique PSO finds a proper place for node deploys, but the finding of SH node is not quick. The PSO technique shows better results when compared to LEACH, but the energy consumption rate is not static. According to the network load and the number of nodes the energy consumption level is changed. The drastically changes creates a problem, where the node looses their energy level in a quick way. The proposed technique helps to find the optimal path for carrying the node placement. In fig 4 the energy consumed by Sinkhole nodes were shown, the first technique LEACH couldn’t find the sinkhole node quickly in a network. This makes the sinkhole node to consume more energy and nodes in a network can't have proper message communication. The second technique PSO can find the optimal path easily when compared to previous technique. But the problem faced by PSO is, they don’t have an ability to reduce the energy consumption of SH node. But the third technique gives an optimal placement and path for message communication between the nodes is done in an effective way. The message forwarding is carried in a secured way and the energy consumed by SH is less when compared with other two techniques. The packet delivery is an important factor in WSN, where the existing technique is not quick to identify the sinkhole node in a network. The fig 5 has the same issue where the probability of finding SH node is less and the packet delivery ratio is high when compared to LEACH and PSO. EABC helps to increase the PDR by finding the SH node at initial stage. The network load and the energy consumed by SH node is less when EABC is deployed in a network. The packet loss in a network is less while using EABC, where both the existing technique fails to reduce the packet loss. The proposed technique has the ability to reduce the packet loss by finding the SH node and avoid that particular node from message communication in the network.

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Figure 3 Avg Energy Consumed for NL=50

Figure 4 Energy consumed by SH for NL=50

Figure 5 PDR for NL=50

5. CONCLUSIONS In this paper we propose a secured algorithm for finding the compromised node in the WSN. In this paper we are going to deploy an Enriched Artificial Bee Colony (EABC) algorithm to detect the sinkhole attacked node in the network and it will be intimated to the base station and the changes in the position of the estimated node should be monitored continuously. To develop an enriched Swarm Intelligence algorithm based on Artificial Bee Colony optimizer, which gives global exploration of multiple paths to transmit data from sensor to sink nodes at the absence of sinkhole nodes. The proposed technique helps the network to find the sinkhole attack in a network. From the above displayed figures we have outlined a set of methods to improve the PDR value in a wireless sensor network. By knowing the risk factor of the sinkhole attack, the proposed technique reacts in an effective way to find the SH node without any delay. To conclude, we want to design some future work for WSN related to security and network topology reconstruction using the EABC. Apart from the sinkhole attacks there are many types of attacks, which has the ability to collapse the network and vulnerable. We strongly believe that by improvising our proposed algorithm by adding some other features will be a nightmare for other security related problems.

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