|dc.description.abstract||Smart Grid is the trend of next generation power distribution and management network that enable interactive communication and operation between consumers and suppliers, so as to achieve intelligent resource allocation management and optimization. The wireless mesh network technology is a promising infrastructure solution to underpin and support these smart functionalities flexibly and scalably, as well as it can provide redundant routes for the smart grid communication network to guarantee the network availability. However, the wireless mesh network infrastructure is vulnerable to some cyber-attacks which need to be addressed. As the Smart Grid is heavily relying on the communication network, it makes these security concerns more critical. There are three major security concerns in the Smart Grid communication network such as network availability, data integrity, and information privacy. The previous security mechanisms such as cryptography, public key infrastructure (PKI), and authentication are the traditional ways to address these security concerns, but there is an emerging research area to discover the alternative solutions on trust and reputation mechanisms for wireless mesh network in Smart Grid environment.
In this thesis, we have proposed and implemented three trust-based geographical routing algorithms to tackle the cyber-attacks in Smart Grid, which are inspired from the existing Ambient Trust Sensor Routing (ATSR) algorithm. The first proposed algorithm, called as Trust-based Intelligent Geo Elective Routing (TIGER), is to resolve the time-insensitive problem in current ATSR by introducing the timestamp. Then the Dynamic Trust Elective Geo Routing (DTEGR) is proposed to tackle the inflexible weight factors selection problem of ATSR using a two-step selection strategy among the forwarding list of neighbours. At last, to advance the flexibility and scalability of TIGER and DTEGR algorithms, the Fuzzy-based Energy Aware Trust Geo Routing (FEATGR) is proposed by using the fuzzy logic approach. It can synthesize the trust, energy, and distance metrics to calculate one final score as the routing metric for determining the best route between source and destination nodes. The extensive simulation studies have confirmed that our new TIGER algorithm is more time-sensitive to detect then avoid the recent malicious attacks than the existing ATSR algorithm, and the DTEGR algorithm is able to achieve better routing performance in different network scenarios by solving the weight factor issue. The FEATGR algorithm is flexible and scalable to maintain good network performance always upon dynamical network scenarios such as various attack patterns.||en_NZ