Main Reference PaperGA-DoSLD: Genetic Algorithm Based Denial-of-Sleep Attack Detection in WSN, Security and Communication Networks, 2017 [NS2].
  • An efficient Genetic Algorithm (GA) based denial-of-sleep attack detection (GA-DoSLD) algorithm is suggested for analyzing the misbehaviors of the nodes. The suggested algorithm implements a RSA algorithm in the base station (BS) for generating and distributing the key pair among the sensor nodes. Before sending/receiving the packets, the sensor nodes determine the optimal route using Ad Hoc On-Demand Distance Vector Routing (AODV) protocol and then ensure the trustworthiness of the relay node using the fitness calculation.

+ Description
  • An efficient Genetic Algorithm (GA) based denial-of-sleep attack detection (GA-DoSLD) algorithm is suggested for analyzing the misbehaviors of the nodes. The suggested algorithm implements a RSA algorithm in the base station (BS) for generating and distributing the key pair among the sensor nodes. Before sending/receiving the packets, the sensor nodes determine the optimal route using Ad Hoc On-Demand Distance Vector Routing (AODV) protocol and then ensure the trustworthiness of the relay node using the fitness calculation.

  • To analyze the neighbor information for creating the population.

  • To determine the optimal route using AODV.

  • To determine the behavior of the already existing attacker by estimating the fitness value

  • To provide an alert message to the base station regarding the behavior of the Neighbor node.

  • To improve the detection accuracy

+ Aim & Objectives
  • To analyze the neighbor information for creating the population.

  • To determine the optimal route using AODV.

  • To determine the behavior of the already existing attacker by estimating the fitness value

  • To provide an alert message to the base station regarding the behavior of the Neighbor node.

  • To improve the detection accuracy

  • During the attack, not only source, the router may falsely injects the packets. It will lead to the false classification of genuine source as attacker. Hence during behavior monitoring packets reception and forwarding statistics are collected to accurately detect the attacker.

+ Contribution
  • During the attack, not only source, the router may falsely injects the packets. It will lead to the false classification of genuine source as attacker. Hence during behavior monitoring packets reception and forwarding statistics are collected to accurately detect the attacker.

  • Operating System : Ubuntu 12.04 LTS 64bit

  • Simulator: NS 2.35, Language : TCL and AWK Script, (C++)

+ Software Tools & Technologies
  • Operating System : Ubuntu 12.04 LTS 64bit

  • Simulator: NS 2.35, Language : TCL and AWK Script, (C++)

  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

+ Project Recommended For
  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-Depending on the complexity of the project and requirements.

+ Order To Delivery
  • No Readymade Projects-Depending on the complexity of the project and requirements.

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