The energy sector is undergoing a period of technological transformation, driven by the emergence of blockchain and smart contracts. These technologies have the potential to revolutionize energy markets and significantly reduce transaction costs, improve efficiency, and increase transparency. The rising energy prices in recent years have been a cause for global concern. As the EU recorded historically high energy prices in 2022, according to the EU Council, this price rise is linked to increased energy demand following the COVID-19 pandemic, the war in Ukraine, and the acceleration of climate change. This paper aims to critically examine the current state of blockchain and smart contracts technology in the energy sector, focusing on use cases, key challenges, and potential solutions. It further explores the impact of these technologies on energy markets and their potential to contribute to a sustainable, low-carbon energy future. Finally, it examines the prospects of blockchain and smart contract technologies to transform the energy industry and the policy implications for governments and regulators.

Over the last decade, learning theory performed significant progress in the development of sophisticated algorithms and their theoretical foundations. The theory builds on concepts that exploit ideas and methodologies from mathematical areas such as optimization theory. Regularization is probably the key to address the challenging problem of overfitting, which usually occurs in high-dimensional learning. Its primary goal is to make the machine learning algorithm “learn” and not “memorize” by penalizing the algorithm to reduce its generalization error in order to avoid the risk of overfitting. As a result, the variance of the model is significantly reduced, without substantial increase in its bias and without losing any important properties in the data.

Phishing emails are malicious email messages that aim to deceive users into revealing sensitive information by imitating legitimate emails. These emails are usually among the first steps in most cyberattacks, often appearing as an urgent message, seemingly from reputable sources, in order to provoke an immediate action from the recipient. Their manipulative nature leverages social engineering techniques to exploit human psychological weaknesses, personality traits, and a range of cognitive, behavioral, and technical vulnerabilities. In this review, the factors that contribute to users’ susceptibility to phishing attacks were investigated. The study focuses on exploring how demographic and psychological factors influence individuals’ vulnerability to phishing emails, with the goal of identifying and categorizing the key factors that increase susceptibility. Twenty-seven studies were examined, revealing that demographic factors, behavioral tendencies, psychological traits and contextual elements play a key role on the users’ susceptibility in phishing emails. The results vary according to the type of methodology that has been used, indicating a need for further investigation and refinement in each respective procedure. Significant investigation has been conducted in identifying the factors contributing to users’ susceptibility to phishing emails, and existing studies do not fully cover the complexity of the topic. There is more to be studied regarding these factors, especially in understanding their complex interactions and impacts across different contexts. Further research is essential so that we may be able to more accurately predict users’ characteristics and the factors that make someone more susceptible to phishing and thus more vulnerable to phishing email attacks.