With the advancement of cyber threats, blockchain technology has evolved to have a significant role in providing secure and reliable decentralized applications. One of these applications is a remote voting system that allow voters to participate in elections remotely. This work proposes a privacy-preserving e-voting system supporting score voting using blockchain technology. The main challenge with score voting compared to the regular yes/no voting approach is that a voter is allowed to assign a score from a defined range for each candidate. To preserve privacy, votes shall be encrypted before submission to the Blockchain, however, a malicious voter can modify the score value before encrypting it to manipulate the elections result for the favor of a certain candidate. To address this challenge, the proposed scheme allows voters to first prove that the submitted score lies in the predefined range before the vote is added to the Blockchain to ensure fairness of the election. The performance of our scheme is evaluated against a set of comprehensive experiments designed to determine optimal bounds for workload and transaction send rates and measure the impact of exceeding these bounds on critical performance metrics. The results of these simulations and their implications therefore indicate that the proposed scheme is secure while being able to handle up to 10,000 transactions at a time.

As Smart City (SC) infrastructures evolve rapidly, securing critical systems like smart water management (SWM) becomes paramount to protecting against cyber threats. Enhancing the security, sustainability and execution of conventional schemes is considered significant in developing smart environments. Intrusion detection systems (IDS) can be effectively leveraged to realise this security objective in an Internet of Things (IoT)‐based smart environment. This research addresses this need by proposing a novel IDS model called TabNet architecture optimised using Sailfish Optimisation (SFO). The TabNet‐SFO model was specifically developed for SWM in SC applications. The proposed IDS model includes data collection, preprocessing, feature selection and classification processes. For training the model, this research used the CIC‐DDoS‐2019 dataset, and for evaluation, real‐time data collected using an IoT‐based smart water metre are used. The preprocessing step eliminates unnecessary features, cleans the data, encodes labels and normalises the applied datasets. After preprocessing, the TabNet model selects significant features in the dataset. The TabNet architecture was optimised using the SFO algorithm, which allows hyperparameter tuning and model optimisation. The proposed model demonstrated improved detection accuracy and efficiency on both the simulated and real‐time datasets. The model attained a 98.90% accuracy, a 98.85% recall, a 98.80% precision, a 98.82% specificity and a 98.78% f1 score on the CIC‐DDoS dataset and a 99.21% accuracy, a 99.02% recall, a 99.05% precision, a 99.10% specificity and a 99.18% f1 score on real‐time data. Compared to existing models, the TabNet‐SFO model outperformed all existing models in terms of performance metrics and validated its efficiency in detecting attacks.

The supervisory control and data acquisition (SCADA) is a combined system of elements of hardware and software that is used for controlling industrial processes either remotely or locally. It also useful for monitoring, gathering and processing real time data, and directly interacting with different electronic as well as integrated devices such as valves, pumps, motors, and sensors. Over the years, it has become increasingly interconnected with the internet, making it vulnerable to cyber threats. In order to contain the system's internet attacks, various methods have been used, especially the encryption techniques such as symmetric and asymmetric approaches as well as the decoy SCADA method. However, with the arrival more advanced security threats such as those based on quantum computing, there is a need to introduce security measures that can neutralize such threats. One promising method is quantum cryptography, which is an encryption technique based on quantum mechanics theories. In this study, a quantum-cryptography-based algorithm is proposed. It is based on the QKD and hash-based signature scheme, which act as key generators and authenticators respectively. In order to evaluate the algorithm's performance, it is subjected to a random substitute and intercept resend attack. Using the probabilistic model checker tool, the probability of succumbing to the two attacks is checked. The results show that the algorithm would significantly improve SCADA's resistance against quantum and classical cyber threats.