The use of sensors and actuators as a form of controlling cyber-physical systems in resource networks has been integrated and referred to as the Internet of Things (IoT). However, the connectivity of many stand-alone IoT systems through the Internet introduces numerous cybersecurity challenges as sensitive information is prone to be exposed to malicious users. This paper focuses on the improvement of IoT cybersecurity from an ontological analysis, proposing appropriate security services adapted to the threats. The authors propose an ontology-based cybersecurity framework using knowledge reasoning for IoT, composed of two approaches: (1) design time, which provides a dynamic method to build security services through the application of a model-driven methodology considering the existing enterprise processes; and (2) run time, which involves monitoring the IoT environment, classifying threats and vulnerabilities, and actuating in the environment ensuring the correct adaptation of the existing services. Two validation approaches demonstrate the feasibility of our concept. This entails an ontology assessment and a case study with an industrial implementation.

The diversity of wireless technologies, connected to the Internet and the more powerful and smaller embedded devices, allows to encompass services to improve everyday activities around us through new applications and businesses. This context emerged with the Internet of Things (IoT), where different technologies connected with the Internet provide several applications to change people's lifestyle. However, such integration of heterogeneous devices causes many problems of security and privacy due vulnerabilities of technologies, carrying important consequences to the users of IoT technologies. In this context, we proposed a reference ontology (IoTSec) with security concepts of M2M communications to help find secure solutions to the IoT environment. We followed a literature review and MENTOR methodology to gather and harmonize security ontologies and knowledge of vulnerabilities, which are the root causes for problems of all information security. In order to elucidate our approach, we describe a case study about the applicability of IoTSec in the industrial scenario.

Business opportunities have been benefited with the popularization of wireless devices of the Internet of Things (IoT). Several security issues can produce drawback to the companies because of Internet technologies did not designed to support IoT as well as information disclosure, privacy issues, and cyber threats. However, these situations of the interest could provide knowledge about the reality of the IoT environment. The monitoring of the elements status of a system involves the Situation Awareness (SA) paradigm. However, a limitation of this model is that SA is awareness held exclusively by the human. In this paper, we propose the adoption of a reference ontology to enhance cybersecurity in the IoT considering SA. An ontology extension is used to deal with distinct situational sources and enrich the meaning around security issues. To validate this proposal we describe a case study considering the data collection from smart objects in a metalworking company.

Measurement mechanisms have steadily evolved over the last years and are a key tool for Network Management. These mechanisms produce results for several network metrics and can be used in different contexts by network administrators. However, the deployment and operation of measurement mechanisms consumes valuable computational and human resources. In this context, approaches to help the administrators to control measurement mechanisms are of paramount importance. In this context, network-wide approaches for such control can provide a larger impact than single device ones. The purpose of this paper is to look at initiatives on the network-wide approaches to control measurement mechanisms in order to provide an integrated perspective. Moreover, we describe criteria that can be used to analyze and compare these initiatives. Furthermore, future trends are discussed in order to predict what the future holds for network-wide control of measurement mechanisms.