An Energy Aware and Secure MAC Protocol for Tackling Denial of Sleep Attacks in Wireless Sensor Networks

Wireless sensor networks which form part of the core for the Internet of Things consist of resource constrained sensors that are usually powered by batteries. Therefore, careful energy awareness is essential when working with these devices. Indeed,the introduction of security techniques such as authentication and encryption, to ensure confidentiality and integrity of data, can place higher energy load on the sensors. However, the absence of security protection c ould give room for energy drain attacks such as denial of sleep attacks which have a higher negative impact on the life span ( of the sensors than the presence of security features. This thesis, therefore, focuses on tackling denial of sleep attacks from two perspectives A security perspective and an energy efficiency perspective. The security perspective involves evaluating and ranking a number of security based techniques to curbing denial of sleep attacks. The energy efficiency perspective, on the other hand, involves exploring duty cycling and simulating three Media Access Control ( protocols Sensor MAC, Timeout MAC andTunableMAC under different network sizes and measuring different parameters such as the Received Signal Strength RSSI) and Link Quality Indicator ( Transmit power, throughput and energy efficiency Duty cycling happens to be one of the major techniques for conserving energy in wireless sensor networks and this research aims to answer questions with regards to the effect of duty cycles on the energy efficiency as well as the throughput of three duty cycle protocols Sensor MAC ( Timeout MAC ( and TunableMAC in addition to creating a novel MAC protocol that is also more resilient to denial of sleep a ttacks than existing protocols. The main contributions to knowledge from this thesis are the developed framework used for evaluation of existing denial of sleep attack solutions and the algorithms which fuel the other contribution to knowledge a newly developed protocol tested on the Castalia Simulator on the OMNET++ platform. The new protocol has been compared with existing protocols and has been found to have significant improvement in energy efficiency and also better resilience to denial of sleep at tacks Part of this research has been published Two conference publications in IEEE Explore and one workshop paper

Analysis of Black hole Attack in Ad hoc On-Demand Distance Vector (AODV) Routing Protocol : Vehicular Ad-hoc Networks (VANET) Context

In past years, popularity of Mobile Ad hoc Networks has led to the conception of Vehicular Ad hoc Networks. These networks must be highly secure before their implementation in real world. One of the vital aspects of these networks is routing protocol. Most of the protocols in VANET acknowledge all nodes in a network to be genuine by default. But there might be malicious nodes which can make the network vulnerable to various attacks. One such attacks is a black hole attack on AODV routing protocol. Because of its popularity, AODV and black hole attack are taken into consideration for this thesis. The aim of the thesis is to analyze effects of black hole attack on AODV and understand security need of routing protocols in VANET. The experimentation for this thesis was performed with 40, 60 and 80 nodes in network simulator (NS). The performance metrics such as average throughput, end to end delay and packet delivery ratio of each assumed scenarios under blackhole attack and with prevention method are calculated. The obtained calculations are compared to analyze the network performance of AODV. The results from the simulator demonstrate that overall network performance of AODV increased with black hole prevention algorithm in comparison to AODV under black hole attack only. Out of all the performance metrics that are used to analyze the network performance, the average throughput of AODV is significantly increased by 21 percent (approximately) when the mitigation algorithm is applied. The prevention approach used for the thesis can make AODV perform better against black hole attack. However, this approach is limited to a small to medium sized networks only