The Internet of Things (IoT) is rapidly spreading, reaching a multitude of different domains, including personal health care, environmental monitoring, home automation, smart mobility, and Industry 4.0. As a consequence, more and more IoT devices are being deployed in a variety of public and private environments, progressively becoming common objects of everyday life. It is hence apparent that, in such a scenario, cybersecurity becomes critical to avoid threats like leakage of sensible information, denial of service (DoS) attacks, unauthorized network access, and so on. Unfortunately, many low-end IoT commercial products do not usually support strong security mechanisms, and can hence be target of-or even means for-a number of security attacks. The aim of this article is to provide a broad overview of the security risks in the IoT sector and to discuss some possible counteractions. To this end, after a general introduction to security in the IoT domain, we discuss the specific security mechanisms adopted by the most popular IoT communication protocols. Then, we report and analyze some of the attacks against real IoT devices reported in the literature, in order to point out the current security weaknesses of commercial IoT solutions and remark the importance of considering security as an integral part in the design of IoT systems. We conclude this article with a reasoned comparison of the considered IoT technologies with respect to a set of qualifying security attributes, namely integrity, anonymity, confidentiality, privacy, access control, authentication, authorization, resilience, self organization.

The availability of cheap and easy-to-install sensors is bolstering the development of monitoring applications in IoT scenarios. Although there is a need for periodical measurements of the tracked signals to guarantee an accurate representation at the receiver, choosing an appropriate duration for the reporting window is not trivial. In fact, the energy restrictions of many devices and the interference caused by other users call for longer reporting windows. However, this causes a higher reconstruction error due to the lower sampling resolution, which may be unacceptable in some applications. We propose a probabilistic random channel access scheme for battery-powered devices which monitor time-correlated phenomena and report their measurements to a fusion center. Our goal is to minimize the energy consumption of the sensors, while guaranteeing that the error in the signal estimate at the receiver does not exceed a chosen threshold. We exploit Markov chains and stochastic geometry to characterize the interference caused by the other devices. The numerical evaluation proves that our scheme is scalable and may be used in highly dense scenarios, and that it outperforms other state-of-the-art approaches, which do not consider the impact of interference on both the energy consumption and the accuracy of data representation.

Monitoring applications are gaining a lot of momentum in the Internet of Things (IoT), bolstered by the availability of cheap and easy-to-install sensors. Often, random access schemes are preferred to coordinated ones because they are more flexible and have no synchronization overhead. The possibility of collisions with other packets and the limited energy availability of the battery-powered nodes demand strategies to reduce the number of transmissions. This, however, is counterbalanced by the need to accurately monitor the process of interest, which requires a sufficient amount of sensed data. In this study, we propose a novel compression and transmission strategy with the objective of prolonging sensors' lifetime while guaranteeing a desired reconstruction accuracy of the tracked data. We consider the effect of both sensing and transmissions on the energy consumption, and adapt the sampling and transmission rates based on the target estimation accuracy and on the probability of packet losses caused by the interference from other sensors.