Security Evaluation of Companion Android Applications in IoT: The Case of Smart Security Devices.

Smart security devices, such as smart locks, smart cameras, and smart intruder alarms are increasingly popular with users due to the enhanced convenience and new features that they offer. A significant part of this convenience is provided by the device's companion smartphone app. Information on whether secure and ethical development practices have been used in the creation of these applications is unavailable to the end user.

Modularity-aware graph autoencoders for joint community detection and link prediction.

Graph autoencoders (GAE) and variational graph autoencoders (VGAE) emerged as powerful methods for link prediction. Their performances are less impressive on community detection problems where, according to recent and concurring experimental evaluations, they are often outperformed by simpler alternatives such as the Louvain method. It is currently still unclear to which extent one can improve community detection with GAE and VGAE, especially in the absence of node features.

Machine Learning Approaches on High Throughput NGS Data to Unveil Mechanisms of Function in Biology and Disease.

In this review, the fundamental basis of machine learning (ML) and data mining (DM) are summarized together with the techniques for distilling knowledge from state-of-the-art omics experiments. This includes an introduction to the basic mathematical principles of unsupervised/supervised learning methods, dimensionality reduction techniques, deep neural networks architectures and the applications of these in bioinformatics. Several case studies under evaluation mainly involve next generation sequencing (NGS) experiments, like deciphering gene expression from total and single cell (scRNA-seq) analysis; for the latter, a description of all recent artificial intelligence (AI) methods for the investigation of cell sub-types, biomarkers and imputation techniques are described.

Contextualized Filtering for Shared Cyber Threat Information.

Cyber threat information sharing is an imperative process towards achieving collaborative security, but it poses several challenges. One crucial challenge is the plethora of shared threat information. Therefore, there is a need to advance filtering of such information.

An IoT-Based Gamified Approach for Reducing Occupants' Energy Wastage in Public Buildings.

Conserving energy amenable to the activities of occupants in public buildings is a particularly challenging objective that includes associating energy consumption to particular individuals and providing them with incentives to alter their behavior. This paper describes a gamification framework that aims to facilitate achieving greater energy conservation in public buildings. The framework leverages IoT-enabled low-cost devices, to improve energy disaggregation mechanisms that provide energy use and-consequently-wastage information at the device, area and end-user level.