The Internet of Things (IoT) refers to the Internet-like structure of billions of interconnected constrained devices, denoted as “smart objects”. Smart objects have limited capabilities, in terms of computational power and memory, and might be battery-powered devices, thus raising the need to adopt particularly energy efficient technologies. Among the most notable challenges that building interconnected smart objects brings about, there are standardization and interoperability. The use of IP has been foreseen as the standard for interoperability for smart objects. As billions of smart objects are expected to come to life and IPv4 addresses have eventually reached depletion, IPv6 has been identified as a candidate for smart-object communication. The deployment of the IoT raises many security issues coming from (i) the very nature of smart objects, e.g., the adoption of lightweight cryptographic algorithms, in terms of processing and memory requirements; and (ii) the use of standard protocols, e.g., the need to minimize the amount of data exchanged between nodes. This paper provides a detailed overview of the security challenges related to the deployment of smart objects. Security protocols at network, transport, and application layers are discussed, together with lightweight cryptographic algorithms proposed to be used instead of conventional and demanding ones, in terms of computational resources. Security aspects, such as key distribution and security bootstrapping, and application scenarios, such as secure data aggregation and service authorization, are also discussed.

In the emerging Industrial Internet of Things (IIoT) scenario machine-to-machine communication is a key technology to set up environments wherein sensors, actuators, and controllers can exchange information autonomously. However, many current communication frameworks do not provide enough dynamic interoperability and security. Therefore, we propose a novel communication framework, based on MQTT broker bridging, which, in an Industrial IoT scenario, can foster dynamic inter-operability across different production lines or industrial sites, guaranteeing, at the same time, a higher degree of isolation and control over the information flows, thereby increasing the overall security of the whole scenario. The solution we propose does also support dynamic authentication and authorization and has been practically implemented and evaluated in a proper small-scale IIoT testbed, encompassing PLCs, IIoT gateways, as well as MQTT brokers with novel and extended capabilities.The evaluation results demonstrate a linear time complexity for all the considered implementations and bridging modes of the extended brokers. Moreover, all considered access token encapsulation techniques demonstrate a minimum overhead in comparison with standard MQTT brokers.

Anomaly detection in network traffic is a hot and ongoing research theme especially when concerning IoT devices, which are quickly spreading throughout various situations of people’s life and, at the same time, prone to be attacked through different weak points. In this paper, we tackle the emerging anomaly detection problem in IoT, by integrating five different datasets of abnormal IoT traffic and evaluating them with a deep learning approach capable of identifying both normal and malicious IoT traffic as well as different types of anomalies. The large integrated dataset is aimed at providing a realistic and still missing benchmark for IoT normal and abnormal traffic, with data coming from different IoT scenarios. Moreover, the deep learning approach has been enriched through a proper hyperparameter optimization phase, a feature reduction phase by using an autoencoder neural network, and a study of the robustness of the best considered deep neural networks in situations affected by Gaussian noise over some of the considered features. The obtained results demonstrate the effectiveness of the created IoT dataset for anomaly detection using deep learning techniques, also in a noisy scenario.

MQTT-Auth: a Token-based Solution to Endow MQTT with Authentication and Authorization Capabilities

The Internet of Things (IoT) is of continuously growing interest for research and industry