A Social Inspired Broker for M2M Protocols

Internet of things can be viewed as the shifting from a network of computers to a network of things.To support M2M communication, several protocols have been developed; many of them are endorsed by client-broker model with a publish-subscribe interaction mechanism. In this paper we introduce a multi broker solution where the network of brokers is inspired by social relationships. This allow data sharing among several IoT systems, leads to a reliable and effective query forwarding algorithm and the small world effect coming from mimic humans relations guarantees fast responses and good query recall

An overview of IoT architectures, technologies, and existing open-source projects

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract]: Today’s needs for monitoring and control of different devices in organizations require an Internet of Things (IoT) platform that can integrate heterogeneous elements provided by multiple vendors and using different protocols, data formats and communication technologies. This article provides a comprehensive review of all the architectures, technologies, protocols and data formats most commonly used by existing IoT platforms. On this basis, a comparative analysis of the most widely used open source IoT platforms is presented. This exhaustive comparison is based on multiple characteristics that will be essential to select the platform that best suits the needs of each organization.This research/work has been supported by GAIN (Galician Innovation Agency) and the Regional Ministry of Economy, Employment and Industry, Xunta de Galicia under grant COV20/00604 through the ERDF Galicia 2014-2020; and by grant PID2019-104958RB-C42 (ADELE) funded by MCIN/AEI/10.13039/501100011033 . Funding for open access charge: Universidade da Coruña/CISUG.Xunta de Galicia; COV20/0060

Internet of Things security with machine learning techniques:a systematic literature review

Abstract. The Internet of Things (IoT) technologies are beneficial for both private and businesses. The growth of the technology and its rapid introduction to target fast-growing markets faces security challenges. Machine learning techniques have been recently used in research studies as a solution in securing IoT devices. These machine learning techniques have been implemented successfully in other fields. The objective of this thesis is to identify and analyze existing scientific literature published recently regarding the use of machine learning techniques in securing IoT devices. In this thesis, a systematic literature review was conducted to explore the previous research on the use of machine learning in IoT security. The review was conducted by following a procedure developed in the review protocol. The data for the study was collected from three databases i.e. IEEE Xplore, Scopus and Web of Science. From a total of 855 identified papers, 20 relevant primary studies were selected to answer the research question. The study identified 7 machine learning techniques used in IoT security, additionally, several attack models were identified and classified into 5 categories. The results show that the use of machine learning techniques in IoT security is a promising solution to the challenges facing security. Supervised machine learning techniques have better performance in comparison to unsupervised and reinforced learning. The findings also identified that data types and the learning method affects the performance of machine learning techniques. Furthermore, the results show that machine learning approach is mostly used in securing the network

IoT (Internet of Things) Podemos Confiar?

A IoT (Internet of Things), consiste num conjunto de vários tipos de software e de hardware que comunicam entre si (M2M), tendo o número de dispositivos aumentado, significativamente, nos últimos anos. Com a IoT é feito o tratamento de dados de sensores, como por exemplo, por sensores de luz, CO2, de presença, entre outros. Dependendo da informação dos sensores, o sistema pode causar a realização de uma ação, desde ativar motores, a notificar o administrador do sistema. Num mundo conectado entre si pela Internet, a confiança que existe na IoT pode diminuir devido à falta de segurança e de privacidade. O principal foco desta dissertação é analisar se os utilizadores de IoT têm confiança na plataforma, olhando principalmente para a segurança e para a privacidade, tendo como metodologia a análise de documentos e a realização de um questionário, a vários utilizadores de dispositivos de IoT. Nesta dissertação, foi criado um questionário, para tentar perceber o nível de confiança que as pessoas têm na IoT. No total, 84 pessoas responderam ao questionário. Podemos concluir com o questionário, que a maioria dos utilizadores tem receios sobre os dispositivos IoT. Os pontos que mais interferem com a confiança, de acordo com o questionário, são a segurança, a privacidade e a transparência que a marca induz no produto IoT.The IoT (Internet of Things) consists of various types of software and hardware that communicate with each other (M2M), and the number of devices has increased significantly in recent years. With IoT, sensor data is processed, for example, by light, CO2, and presence sensors, among others. Depending on the information from the sensors, the system can cause an action to be performed, from activating motors to notifying the system administrator. In a world connected through the Internet, the trust in the IoT can diminish due to a lack of security and privacy. The main focus of this dissertation is to analyze whether IoT users trust the platform, looking mainly at security and privacy, with the methodology of analyzing documents and conducting a questionnaire to several users of IoT devices. In this dissertation, a questionnaire was created to try to understand the level of trust people have in the IoT. In total, 84 people answered the questionnaire. We can conclude from the questionnaire that most users fear IoT devices. According to the questionnaire, the points that most interfere with trust are security, privacy and the brand's transparency in the IoT product.info:eu-repo/semantics/publishedVersio