A NetLogo simulation tool for UAV-based secure location verification in crowd sensing

In the last decade, Unmanned Aerial Vehicle (UAV) production and interest is observing a continuous growth that appears not to decline. Meanwhile, thanks to the increase in the use of personal mobile devices and their onboard sensors, which is becoming more and more widespread, a new data collection technique, named crowd sensing, has emerged. Unfortunately, security remains a relevant issue, chiefly the integrity, i.e. the assurance that the information reported is trustworthy and accurate, still remains unsolved. The information the participant declares could be inaccurate or even counterfeit, due to flaws or fraud. Current literature shows no efficient solutions to the security problem, hence the arising need to point in this direction. The idea of this thesis came from the merging of the aforementioned mobile technologies. The aim is to fill the security gap in the crowd sensing process through UAVs employment, to prove trustworthiness and accuracy of sensorial data. The project presumes UAVs expedition in swarms where the data is originated, the authenticity of which could be promptly and directly verified thanks to the onboard sensors and, possibly, through interaction with other close sensors. Through the deployment of a simulator, written in the NetLogo language, it has been possible to reproduce a crowd sensing system and investigate the trustworthiness gap. We proposed and compared two different decision criteria to reveal attacks, named Dictatorship and Majority, both based on distance evaluation through radio frequency communication with the participant. In Dictatorship, it is sufficient that one UAV detects an inconsistency to warn an attack. In Majority, the half plus one of UAVs must detect an inconsistency in order to warn an attack. With regard to that, Dictatorship criterion showed certainly a better performance than Majority one. We further focused on participants' waiting time reduction acting on the algorithms to schedule swarms missions. A First Come First Served (FCFS)-like routine and an Insertion heuristic have been deployed. Since there are no statistical differences between the two for the tests we performed, the former scheduling algorithm is preferable due to its deterministic nature

A Trusted Platform for Unmanned Aerial Vehicle-Based Bridge Inspection Management System

Bridge inspection has a pivotal role in assuring the safety of critical structures constituting society. However, high cost, worker safety, and low objectivity of quality are classic problems in traditional visual inspection. Recent trends in bridge inspection have led to a proliferation of research utilizing Unmanned Aerial Vehicles (UAVs). This thesis proposes a Trusted Platform for Bridge Inspection Management System (Trusted-BIMS) for safe and efficient bridge inspection by proving the UAV-based inspection process and improving the prototype of the previous study. Designed based on a Zero-Trust (ZT) strategy, Trusted-BIMS consist of (1) a database-driven web framework with security features for bridge inspection management, (2) a mobile interface supporting the inspection data collection using UAVs, and (3) a mutual authentication protocol for the Internet of Things (IoTs). The server script language used to implement the web system was PHP and React Native was used for the mobile application development. The secure communication algorithm used server-side PHP and client-side JavaScript, and MySQL was adopted as the database. This paper provides an overview and details of Trusted-BIMS and demonstrates the overall process of bridge inspection using UAVs and applied technologies to the proposed platform. The result of this research will make an important contribution to the field of UAV-based bridge inspection. Further research can be conducted on refined implementations of security algorithms, more comprehensive security schemes, and machine learning technology to reduce human intervention