The “black-box” nature of artificial intelligence (AI) models has been the source of many
concerns in their use for critical applications. Explainable Artificial Intelligence (XAI) is a …

Federated learning is a distributed machine learning approach that enables a large number
of edge/end devices to perform on-device training for a single machine learning model …

Smart contracts struggle with the major limitation of operating on data that is solely residing
on the blockchain network. The need of recruiting third parties, known as oracles, to assist …

In the context of distributed machine learning, the concept of federated learning (FL) has
emerged as a solution to the privacy concerns that users have about sharing their own data …

At present, there is a pressing need for data scientists and academic researchers to devise
advanced machine learning and artificial intelligence-driven systems that can effectively …

Recently, the concept of autonomous driving became prevalent in the domain of intelligent
transportation due to the promises of increased safety, traffic efficiency, fuel economy and …

Intelligent applications are highly susceptible to uncertainty and inconsistency due to the
intense and intricate interactions among their autonomous components (or agents), making …

The rapid integration of the Internet of Things (IoT) with ad hoc networks offers significant
advantages for revolutionizing smart environments. However, ensuring trust and reliability …

Several formal trust frameworks have been introduced in the area of Multi-Agent Systems
(MASs). However, the problem of model checking trust logics is still a challenging research …

Blockchain systems based on smart contracts are critical systems that have to be verified in
order to ensure their reliability and efficiency. Verifying these systems is a major challenge …