This Bachelor's thesis aims to refactor and extend the original Java-based TRMSim-WSN trust simulator for wireless sensor and IoT-like networks, making it compatible with current Java environments while preserving the core functionality of the original system. The updated simulator should provide a practical environment for selecting, testing, and comparing trust models; allow users to define network parameters; collect evidence from peers; perform trust evaluation; and determine peer trustworthiness, including under adversarial conditions and attack scenarios.

The work will include refactoring the original application, improving the user interface, supporting the export of simulation results, and parallel comparison of trust models via concurrent execution of two simulations. The simulator will also support importing and loading predefined WSN scenarios.

The thesis will further address extensibility and scalability. It will analyse drone-oriented predefined scenarios and, where feasible, implement them as functional predefined scenarios. It will also test and evaluate the simulator on larger-scale networks, including networks with 1000 or more nodes, and identify practical limitations of the current implementation. In addition, it will investigate the feasibility of selected machine-learning-based approaches, such as a Bayesian classifier and SVM.

The resulting source code will be made publicly available in the IS in accordance with the license conditions of the original project. Since the thesis builds on and modifies the original TRMSim-WSN codebase, the original copyright and license notices must be preserved. The redistributed and modified code will remain available under the GNU Lesser General Public License, version 3 or later, together with the original additional attribution requirements, and all modifications introduced in the thesis will be clearly marked.