Ambient intelligence is a new paradigm in the Internet of Things (IoT) world that brings smartness to living environments to make them more sensitive; adaptive; and personalized to human needs. A critical area where ambient intelligence can be used is health and social care; where it can improve and sustain the quality of life without increasing financial costs. The adoption of this new paradigm for health and social care largely depends on the technology deployed (sensors and wireless networks), the software used for decision-making and the security, privacy and reliability of the information. IoT sensors and wearables collect sensitive data and must respond in a near real-time manner to input changes. An IoT security framework is meant to offer the versatility and modularization needed to sustain such applications. Our framework was designed to easily integrate with different health and social care applications, separating security tasks from functional ones and being designed with independent modules for each layer (Cloud, gateway and IoT device), that offer functionalities relative to that layer.

Our society finds itself in a point where it becomes more and more bounded by the use of technology in each activity, no matter how simple it could be. Following this social trend, the IT paradigm called Internet of Things (IoT) aims to group each technological end-point that has the ability to communicate, under the same "umbrella". In recent years many private or public organizations have discussed on this topic and tried to provide IoT Platforms that will allow the grouping of devices scattered worldwide. Yet, while information flows and a certain level of scalability and connectivity have been assured, one key component, security, remains a vulnerable point of IoT Platforms. In this paper we describe the main features of some of these “umbrellas”, either open source or with payment, while analyzing and comparing the security solutions integrated in each one of these IoT Platforms. Moreover, through this paper we try to raise users and organizations awareness of the possible vulnerabilities that could appear in any moment, when using one of the presented IoT Platforms.

The current shift towards digital transactions emphasizes the need for robust Qualified Electronic Signature (QES) frameworks that safeguard integrity and privacy. Having the potential to become the leading type of adopted QES, the main challenge that Remote QESs present to end users is choosing between transmitting the entire document or only its digest to the Trust Service Provider (TSP). The first option compromises the document’s confidentiality, while the second one requires the development of signature applications compliant with advanced signature formats, a task that often needs additional time and resources. In this paper, we introduce a comprehensive strategy for remote QESs, designed for seamless integration with current client applications, while simultaneously maintaining user privacy. The main topics approached in this paper are the following: a comprehensive architecture for privacy-aware remote QES systems, relevant standards and legislation, integration scenarios for clients, and remote QES standard protocols to assure communication between client and TSP environments. Furthermore, we also explore the integration of our proposed solution with an enhanced long-term preservation service that uses Ethereum smart contracts and methodologies to implement signature applications with advanced electronic signatures via open-source libraries while ensuring document privacy. The main result of this work is a flexible on-premise module that provides the ability to sign, validate, and preserve documents, with a minimal integration effort.

Recent progress in the fields of networking, communications, computing, hardware and software have revolutionized the way people, smart objects and systems interact and exchange information. The Internet of Things (IoT) and Cyber-Physical Systems (CPS) will fuel the achievement of this new interconnected world. However, the success of these systems strongly depends on the security, privacy and trust of both IoT and CPS, as well as the sensitive data involved. Although these technologies offer many possibilities, the growing hardware and software complexity, as well as the existence of global access, increase the vulnerability to security attacks. This paper presents a testbed for implementing security, privacy and trust in IoT. Existing testbeds and algorithms are reviewed and the enhancements provided by our proposed platform are highlighted. The platform is based on an IoT gateway node that has 3 different hardware architectures (MCU, SDSoC, traditional CPU) integrated in the shape of a single testbed. One of the objectives is to test, optimize and, if doable, develop lightweight cryptographic algorithms to be deployed on the proposed testbed.

In this paper we introduce a continuous authentication system based on keystroke dynamics (BIOMETRIC). We also propose two algorithms for extracting patterns and validating the user, both intended to be used in the same time to improve the overall performance of the validation process. The first one is based on a Multi Layer Perceptron (MLP) Neural Network and the second one relies on a trust algorithm that uses the Bhattacharyya coefficient.

Our hypothesis is that in order to extract relevant information from a sensor network placed to monitor or control urban behavior, the data received has to be first manipulated to determine the most impactful components and then analyzed. At urban construction sites, huge numbers of automatic monitoring sensors are installed in the influence zone of the construction along the city, above ground and underground. We calculated that quite often sensors are damaged or cannot transfer their data temporarily. In these cases, safety-relevant data is lost quite often making data interpretation impossible. This paper presents a method to solve more efficiently the often occurring `missing data' problem when monitoring under difficult urban environmental conditions, compared to existing solutions. The main contribution of the paper consists in evaluating the challenges of monitoring urban environments and designing an advanced sensing system for water infrastructures.