In the modern era, the use of blockchain technology has been growing rapidly, where Ethereum smart contracts play an important role in securing decentralized application systems. However, these smart contracts are also susceptible to a large number of vulnerabilities, which pose significant threats to intelligent systems and IoT applications, leading to data breaches and financial losses. Traditional detection techniques, such as manual analysis and static automated tools, suffer from high false positives and undetected security vulnerabilities. To address these problems, this paper proposes an Artificial Intelligence (AI)-based security framework that integrates Generative Adversarial Network (GAN)-based feature selection and deep learning techniques to classify and detect malware attacks on smart contract execution in the blockchain decentralized network. After an exhaustive pre-processing phase yielding a dataset of 40,000 malware and benign samples, the proposed model is evaluated and compared with related studies on the basis of a number of performance metrics including training accuracy, training loss, and classification metrics (accuracy, precision, recall, and F1-score). Our combined approach achieved a remarkable accuracy of 97.6%, demonstrating its effectiveness in detecting malware and protecting blockchain systems.

In the era of modern societies and smart cities, Intelligent Transport Systems (ITS) are becoming increasingly complex and interconnected. ITS aims at integrating sensing, control, analysis, and communication technologies into travel infrastructure and urban transport to improve mobility, comfort, and efficiency. However, these systems are vulnerable to a variety of malicious cyberattacks that have a significantly dangerous influence on the security, integrity, and availability of data exchange, causing traffic disruption, accidents, and financial losses. Traditional centralized security solutions are often inadequate to address these threats. Thus, blockchain technology, with its decentralized, transparent, and immutable nature, offers a promising alternative for improving security in ITS. This paper explores the potential of ethereum blockchain based smart contracts to enhance security in ITS. We discuss how smart contracts can be used to strengthen security and pave the way for a safer, efficient, and resilient transport environment. Our approach will be applied on different scenarios as a representative case study of ITS environment. So far, quantitative and qualitative evaluations of the architecture under common threat models highlight its effectiveness in providing security, transparency, and availability.