Abstract:Abstract.The ease of deployment of economic sensor networks has always been a boon to disaster management applications. However, their vulnerability to a number of security threats makes communication a challenging task. This paper proposes a new routing technique to prevent from both external threats and internal threats like hello flooding, eavesdropping and wormhole attack. In this approach one way hash chain is used to reduce the energy drainage. Level based event driven clustering also helps to save energ… Show more
“…In other words, the network life is inversely proportional to the K value. In addition, compared with frequency-domain signal-space projection (FDSSP), FDA, 10 and virtual private network life (VP-NL), 5 the network life of KMGA has been improved, the reason of which is that the KMGA model balances energy consumption and further ensures that all sensor nodes are at the same level of energy consumption.…”
Section: Experimental Analysis and Discussionmentioning
confidence: 99%
“…These sensors organize themselves into groups, which are called Sensor Covers (SCs), which are responsible for monitoring targets. A typical target coverage algorithm assumes that the environment parameters are known and the optimal SCs are searched by these coverage algorithms to ensure that each sensor covers one target 5,6 so as to extend the network life. However, if sensor nodes fail, for example, energy consumption is exhausted, these algorithms will no longer be scalable.…”
Wireless sensor networks have been widely used in target monitoring application. It is often assumed in a typical target coverage algorithm that the environment is known, and each target is covered by only one node. However, these algorithms are not scalable. In fact, one target may need to be covered by more than one node, which is the K-coverage problem. Aiming at the application of target monitoring in wireless sensor network, a K-coverage model— kernal matrix based genetic algorithm (KMGA) based on the genetic algorithm—is proposed. The KMGA model ensures that each target is covered by multiple sensors simultaneously. First, multiple Covers are generated as much as possible through genetic algorithm, and then, while coverage requirements are ensured, coverage between Covers is switched based on remaining energies of nodes so as to extend the network life. Experimental data show that the proposed KMGA model can effectively extend the network lifetime and ensure coverage rate.
“…In other words, the network life is inversely proportional to the K value. In addition, compared with frequency-domain signal-space projection (FDSSP), FDA, 10 and virtual private network life (VP-NL), 5 the network life of KMGA has been improved, the reason of which is that the KMGA model balances energy consumption and further ensures that all sensor nodes are at the same level of energy consumption.…”
Section: Experimental Analysis and Discussionmentioning
confidence: 99%
“…These sensors organize themselves into groups, which are called Sensor Covers (SCs), which are responsible for monitoring targets. A typical target coverage algorithm assumes that the environment parameters are known and the optimal SCs are searched by these coverage algorithms to ensure that each sensor covers one target 5,6 so as to extend the network life. However, if sensor nodes fail, for example, energy consumption is exhausted, these algorithms will no longer be scalable.…”
Wireless sensor networks have been widely used in target monitoring application. It is often assumed in a typical target coverage algorithm that the environment is known, and each target is covered by only one node. However, these algorithms are not scalable. In fact, one target may need to be covered by more than one node, which is the K-coverage problem. Aiming at the application of target monitoring in wireless sensor network, a K-coverage model— kernal matrix based genetic algorithm (KMGA) based on the genetic algorithm—is proposed. The KMGA model ensures that each target is covered by multiple sensors simultaneously. First, multiple Covers are generated as much as possible through genetic algorithm, and then, while coverage requirements are ensured, coverage between Covers is switched based on remaining energies of nodes so as to extend the network life. Experimental data show that the proposed KMGA model can effectively extend the network lifetime and ensure coverage rate.
“…Secure Energy-Efficient Routing (SEER) authenticates data using a one-way hash chain and uses a shared secret key between the mobile node and the base station to improve confidentially [32]. is technique creates a tree based on the base station and initializes the one-way hash chain.…”
MANET is utilized in many fields because of its advantage in quickly establishing networks. The network will perform well if mobile nodes trust each other and act cooperatively. However, dynamic topology characteristics and frequent connection failures by the movement of nodes make routing difficult and cause vulnerability to be easily exposed. Therefore, the routing provided in the MANET should have security features that can reduce the damage to various attacks. For this, in this paper, it is proposed for a trust evaluation method of nodes using cluster structure and a secure data transmission technique through key exchange without CA. The proposed technique adopted a hierarchical structure to enhance the efficiency of the reliability evaluation of nodes. The reliability measurement reflects the quality of packets as well as the number of packets and the measured reliability is maintained by the trust management node. The integrity of the data transmission is improved through key exchange without CA between the nodes. In order to increase the efficiency of routing, anomaly nodes are detected by DSN checking of nodes that generate excessive traffic on the path when data is transmitted. The proposed technique in this paper can maintain stably the network performance even in the presence of malicious nodes because it ensures reliability evaluation for nodes and the path setting between nodes and secure data transmission. The superior performance of the proposed trust-based model security routing technique was confirmed through comparative experiments for packet delivery ratio, end-to-end delay time, the number of control packets, network throughput, and average path length.
“…The study of Das, et al; [4] most recently introduced a WSN driven threat modeling system to bring resistance against wormhole as well as flooding attacks. Moreover, the study adopted the features of MAC scheme to ensure optimal security management in a WSN.…”
Section: Techniques For Routing Based Securitymentioning
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