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Design and Evaluation of Lightweight Intrusion Detection for Sybil Attack Under Mobile RPL in the Internet of Things

Design and Evaluation of Lightweight Intrusion Detection for Sybil Attack Under Mobile RPL in the Internet of Things

Cooja Lightweight Intrusion Detection Project for Sybil Attack Under Mobile RPL in the Internet of Things

Research Area:

IOT

Research Topics:

Contiki Cooja Simulator Projects in RPL Routing Protocol

Tools Languages:  Contiki-Cooja / Contiki NG simulator, Front End: Java, Back End: C

Software Requirement:  Vmware workstation player, Instant Contiki-3.0

Aim and Objectives:  
Implementing a project is evaluated of lightweight intrusion Detection for Sybil Attack Under Mobile RPL in the Internet of Things.

Contribution:  
1. The main contribution of this project is to create a lightweight intrusion detection algorithm for mobile RPL against the Sybil attack, which needs less computation and provides high accuracy, which is quintessential in the case of a resource-constrained network.
2. To implement a bio-inspired mathematical model for the Sybil attack in mobile RPL based on the Artificial Bee Colony (ABC) model.
3. Examine the effectiveness of the proposed lightweight intrusion detection algorithm.

Performance Evalution:  
This project provided evaluation results corresponding to the DODAG setup phase with the attack model using the cooja simulator. The random-way point model is used for mobility, and at the beginning stage, 80 nodes are positioned arbitrarily in a 300 m by 300m area. When the simulation started, every node was arbitrarily located at random places within the 300 m x 300m area.
Performance Metrics:
 •  PDR
 •  Throughput
 •  CPU Energy Consumption
 •  Control Packet Overhead
 •  Execution Time
 •  Delay
 •  Energy Consumption
 •  Network Lifetime