Trust-based secure routing in MANETs has attracted lot of research attention worldwide. It is effective in providing secure routing by isolating malicious nodes and other overheads from MANETs. This paper proposes, GradeTrust, a secure routing protocol for MANETs based on the trust levels of network nodes. It uses trust to isolate black hole routing attacks thus offering secure routing of data traffic as well as improved packet delivery ratio. Preliminary simulation results have shown that trust compromise and packet delivery ratio is better in GradeTrust compared to traditional routing protocols, such as AODV and FSR.

This research addresses blackhole routing attacks-a fundamental security attack on the routing of data in IoT networks. Most IoT devices today, from medical devices to connected vehicles and even smart buildings, come bundled with the capability of communicating wirelessly with one another. Consumers are progressively embracing the concept of connected devices while recent studies indicate that security is not high on the priority list of manufacturers especially in the way these devices route and communicate data amongst themselves thus, leaving the door wide open to attacks and compromises. We propose a trust-based RPL routing protocol, which addresses the blackhole attacks. We show that our proposed system is both secure from blackhole attacks while not imposing undue overheads on network traffic.

Social engineering attacks are possibly one of the most dangerous forms of security and privacy attacks since they are technically oriented to psychological manipulation and have been growing in frequency with no end in sight. This research study assessed the major aspects and underlying concepts of social engineering attacks and their influence in the New Zealand banking sector. The study further identified attack stages and provided a user-reflective model for the mitigation of attacks at every stage of the social engineering attack cycle. The outcome of this research was a model that provides users with a process of having a reflective stance while engaging in online activities. Our model is proposed to aid users and, of course, financial institutions to re-think their anti-social engineering strategies while constantly maintaining a self-reflective assessment of whether they are being subjected to social engineering attacks while transacting online.

This research proposes a conceptual framework for achieving a secure Internet of Things (IoT) routing that will enforce confidentiality and integrity during the routing process in IoT networks. With billions of IoT devices likely to be interconnected globally, the big issue is how to secure the routing of data in the underlying networks from various forms of attacks. Users will not feel secure if they know their private data could easily be accessed and compromised by unauthorized individuals or machines over the network. It is within this context that we present the design of SecTrust, a lightweight secure trust-based routing framework to identify and isolate common routing attacks in IoT networks. The proposed framework is based on the successful interactions between the IoT sensor nodes, which effectively is a reflection of their trustworthy behavior.