Behrouz Zolfaghari

In recent years, we have witnessed the era of IoT. Extensions of the IoT are found almost everywhere in the modern world: under the ground, on the ground, under the sea, in the sky, and in space. Such a rapid proliferation has given rise to a variety of requirements and challenges. As suggested by the recent literature, security is the most critical challenge in this area. A comprehensive survey in this area can pave the way for further research by highlighting current trends and shedding light on less-studied aspects of the area. This paper provides a comprehensive review of the current state of research on IoT extensions, with a focus on security. We start with reviewing existing relevant surveys, noting their shortcomings. We highlight the lack of inclusiveness in existing surveys. Moreover, we show that these surveys do not look closely at security challenges and fail to develop a taxonomy or a solid future roadmap. Then, we provide an overview of the security challenges and mechanisms of IoT extensions. We proceed to develop a taxonomy of these extensions with a focus on security. Lastly, we discuss what the future may hold for IoT extensions, given the role of artificial intelligence in IoT and the advancements of artificial intelligence on the horizon.

UAVs have found their applications in numerous applications from recreational activities to business in addition to military and strategic fields. However, research on UAVs is not going on as quickly as the technology. Especially, when it comes to the security of these devices, the academia is lagging behind the industry. This gap motivates our work in this article as a stepping stone for future research in this area. A comprehensive survey on the security of UAVs and UAV-based systems can help the research community keep pace with, or even lead the industry. Although there are several reviews on UAVs or related areas, there is no recent survey broadly covering various aspects of security. Moreover, none of the existing surveys highlights current and future trends with a focus on the role of an omnipresent technology such as AI. This article endeavors to overcome these shortcomings. We conduct a comprehensive review on security challenges of UAVs as well as the related security controls. Then we develop a future roadmap for research in this area with a focus on the role of AI. The future roadmap is established based on the identified current trends, under-researched topics, and a future look-ahead.

Ensemble methods try to improve performance via integrating different kinds of input data, features, or learning algorithms. In addition to other areas, they are finding their applications in cancer prognosis and diagnosis. However, in this area, the research community is lagging behind the technology. A systematic review along with a taxonomy on ensemble methods used in cancer prognosis and diagnosis can pave the way for the research community to keep pace with the technology and even lead trend. In this article, we first present an overview on existing relevant surveys and highlight their shortcomings, which raise the need for a new survey focusing on Ensemble Classifiers (ECs) used for the diagnosis and prognosis of different cancer types. Then, we exhaustively review the existing methods, including the traditional ones as well as those based on deep learning. The review leads to a taxonomy as well as the identification of the best-studied cancer types, the best ensemble methods used for the related purposes, the prevailing input data types, the most common decision-making strategies, and the common evaluating methodologies. Moreover, we establish future directions for researchers interested in following existing research trends or working on less-studied aspects of the area.