Due to its scarce energy sources, and the open nature of transmissions in wireless environments, the wide spread of MANETs is challenged by many factors. Energy efficiency and security issues are considered of the utmost factors, security threats are represented by many attacks, one of which is the vicious Black Hole Attack. In Black Hole Attack, malicious nodes try to engage in as many active connections as possible to jeopardize the scarce network resources. To engage in a connection, during the route discover process, the malicious node sends a prompt route reply message to the source node to acknowledge it has an active route to the destination node, and when it receives the data packets it will simply drop it. Black holes jeopardize the network performance in terms of packet delivery ratio and number of dropped packets.Detecting and neutralizing black hole node is an important task to utilize the network resources efficiently. Network devices spend more than 80% of its available power on communication rather than on processing. Designing an energy-efficient detection scheme is vital to prolong the network lifetime as it reduces the amount of traffic transmitted in the network. The proposed mechanism requires a minimal change to the routing protocol and a minimal overhead to the network. The proposed scheme benefits from the open transmission nature of wireless devices (i.e. minimizing energy consumption) and tries to build a cooperative environment to monitor and observe the behaviour of on-going transmission. In the proposed algorithm, the source node utilizes other nodes in the network (called observer node) to detect if the transmission of data packets to next hop is carried. In case of error, the observer node sends an error message (namely, OERR) to the source node. Upon receiving a repetitive OERR messages, the source node marks the observed intermediate node as a black hole. The performance of the proposed scheme is evaluated using simulation. The obtained results indicate the superiority of the proposed scheme. For example, the proposed algorithm enhances the delivery ratio in dense networks by 45.6% and in by 41% in sparse networks. Moreover, it enhances the dropped packet in dense networks by 75%, and by 63% in sparse networks.
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