Abstract Adversarial Machine Learning (AML) is a recently introduced technique, aiming to
deceive Machine Learning (ML) models by providing falsified inputs to render those models …

The timely identification and early prevention of crop diseases are essential for improving
production. In this paper, deep convolutional-neural-network (CNN) models are …

After the Cold War, the defense industries found themselves at a crossroads. However, it
seems that they are gaining new momentum, as new technologies such as robotics and …

Most existing deep neural networks are susceptible to the influence of adversarial examples,
which may cause them to output incorrect prediction results. An adversarial example is the …

The goal of mortality prediction task is to predict the future death risk of patients according to
their previous Electronic Healthcare Records (EHR). The main challenge of mortality …

Featured Application This article recalls the concept of cognitive city and provides a timely
review of the state of the art in the field of information security and privacy for cognitive cities …

Poisson pulse sequence generators are quite well studied, have good statistical properties,
are implemented both in software and hardware, but have not yet been used for the purpose …

Accurate liver vessel segmentation is of crucial importance for the clinical diagnosis and
treatment of many hepatic diseases. Recent state-of-the-art methods for liver vessel …

The fault diagnosis of safety critical systems such as wind turbine installations includes
extremely challenging aspects that motivate the research issues considered in this paper …

Voice user interface (VUI) brings high efficiency and convenience for the applications of
Internet of Things (IoT), meanwhile, it can also cause increasingly serious security issues …