A Group Authentication Protocol on Multilayer Structure for Privacy-Preserving IoT Environment

In the Internet of Things (IoT) systems, large amounts of data are accumulated from anywhere at any time, which may attack individuals' privacy, especially when systems are utilized in medical and everyday environments. With the promise of IoT's proactive systems, the integration of smart things into standard Internet creates several security challenges, because most Internet technologies, communication protocols and sensors are not designed to support IoT. Recent research studies have shown that launching security / privacy attacks against IoT active systems, in particular, Wearable Medical Sensor (WMS) systems, may lead to catastrophic situations and life-threatening conditions. Therefore, security threats and privacy concerns in the IoT area should be actively studied. This causes us in this paper to create a privacy authentication protocol for IoT end-devices on a four-layer structure that does not have the ability to accurately identify the device of request's sender so that some attacks can be minimized. We used the Blakley Sharing scheme to design a key generation and distribution system for secure communications between edge devices and end devices and examined the security properties of the protocol for the five common attacks in the IoT. The results of the experiments show that the proposed authentication protocol by the Blakley method is more efficient with increasing number of instructions in both fog structures and in a without fog structure, which shows a higher flexibility of the Blakley method than the Schemer because of the increasing number of instructions indicating increasing the number of nodes in the network

IoT Security Evolution: Challenges and Countermeasures Review

Internet of Things (IoT) architecture, technologies, applications and security have been recently addressed by a number of researchers. Basically, IoT adds internet connectivity to a system of intelligent devices, machines, objects and/or people. Devices are allowed to automatically collect and transmit data over the Internet, which exposes them to serious attacks and threats. This paper provides an intensive review of IoT evolution with primary focusing on security issues together with the proposed countermeasures. Thus, it outlines the IoT security challenges as a future roadmap of research for new researchers in this domain

Graphs behind data: A network-based approach to model different scenarios

openAl giorno d’oggi, i contesti che possono beneficiare di tecniche di estrazione della conoscenza a partire dai dati grezzi sono aumentati drasticamente. Di conseguenza, la definizione di modelli capaci di rappresentare e gestire dati altamente eterogenei è un argomento di ricerca molto dibattuto in letteratura. In questa tesi, proponiamo una soluzione per affrontare tale problema. In particolare, riteniamo che la teoria dei grafi, e più nello specifico le reti complesse, insieme ai suoi concetti ed approcci, possano rappresentare una valida soluzione. Infatti, noi crediamo che le reti complesse possano costituire un modello unico ed unificante per rappresentare e gestire dati altamente eterogenei. Sulla base di questa premessa, mostriamo come gli stessi concetti ed approcci abbiano la potenzialità di affrontare con successo molti problemi aperti in diversi contesti. ​Nowadays, the amount and variety of scenarios that can benefit from techniques for extracting and managing knowledge from raw data have dramatically increased. As a result, the search for models capable of ensuring the representation and management of highly heterogeneous data is a hot topic in the data science literature. In this thesis, we aim to propose a solution to address this issue. In particular, we believe that graphs, and more specifically complex networks, as well as the concepts and approaches associated with them, can represent a solution to the problem mentioned above. In fact, we believe that they can be a unique and unifying model to uniformly represent and handle extremely heterogeneous data. Based on this premise, we show how the same concepts and/or approach has the potential to address different open issues in different contexts. ​INGEGNERIA DELL'INFORMAZIONEopenVirgili, Luc