Diego Sánchez-de-Rivera

A Methodology for the Design of Application-Specific Cyber-Physical Social Sensing Co-Simulators

Cyber-Physical Social Sensing (CPSS) is a new trend in the context of pervasive sensing. In these new systems, various domains coexist in time, evolve together and influence each other. Thus, application-specific tools are necessary for specifying and validating designs and simulating systems. However, nowadays, different tools are employed to simulate each domain independently. Mainly, the cause of the lack of co-simulation instruments to simulate all domains together is the extreme difficulty of combining and synchronizing various tools. In order to reduce that difficulty, an adequate architecture for the final co-simulator must be selected. Therefore, in this paper the authors investigate and propose a methodology for the design of CPSS co-simulation tools. The paper describes the four steps that software architects should follow in order to design the most adequate co-simulator for a certain application, considering the final users’ needs and requirements and various additional factors such as the development team’s experience. Moreover, the first practical use case of the proposed methodology is provided. An experimental validation is also included in order to evaluate the performing of the proposed co-simulator and to determine the correctness of the proposal.

Detecting Malicious Components in Large-Scale Internet-of-Things Systems and Architectures

Current large-scale Internet-of-Things systems and architectures incorporate many components, such as devices or services, geographic and conceptually very sparse. Thus, for final applications, it is very complicated to deeply know, manage or control the underlying components, which, at the end, generate and process the data they employ. Therefore, new tools to avoid or remove malicious components based only on the available information at high level are required. In this paper we describe a statistical framework for knowledge discovery in order to estimate the uncertainty level associated with the received data by a certain application. Moreover, these results are used as input in a reputation model focused on locating the malicious components. Finally, an experimental validation is provided in order to evaluate the performance of the proposed solution.

Protecting Industry 4.0 Systems Against the Malicious Effects of Cyber-Physical Attacks

Industry 4.0 refers a new industrial paradigm based on Cyber-Physical Systems principles. In these new, complex and highly interdependent systems, the traditional definition of “cyber-attack” is not enough to represent all the situations may occur. Furthermore, traditional security policies and defense strategies are not designed to be effective in scenarios mixing cyber and physical elements. In this context, this work presents a new idea about what cyber-physical attacks are, and a technological solution to protect and compensate the malicious effects of these attacks in Industry 4.0 systems. The proposal is based on a specific description language (CP-ADL) for cyber-physical attacks, and a mathematical framework allowing a decision making about the most adequate defense strategy. Finally, and experimental validation is provided, showing with our proposal the impact of cyber-physical attacks is highly reduced.

Cyber-Physical Sensors and Devices for the Provision of Next-Generation Personalized Services

Cyber-Physical Systems (CPS) are set to radically transform the world we live in. Prototypes for very different domains have been reported, from Industry 4.0 to Ambient Intelligence and the Internet of Things. Several research works have shown the good performance of these systems, which could be useful for everyday living once they become commercial products. However, no complete application for cyber-physical devices has been reported yet. Thus, the large amount of benefits this new paradigm may push remains very difficult to envision by general society and companies. In any case, personalized services rank among the most direct and interesting applications for cyber-physical devices. So far, no work on this topic has been reported, but the implementation of this new generation of services is a key area for the advancement toward the CPS era. Therefore, in this paper we will explore the concept of cyber-physical personalized services and propose a first example of these new services based on cyber-physical sensors and a cyber-physical device: a smart table. Finally, in order to evaluate the performance of the proposed solution, we will carry out an experimental validation.

Low-Level Service Management in Cyber-Physical Systems

First standardization initiatives of the Cyber-Physical Systems (CPS) paradigm face a type of solutions with a top-down approach. In this view, user services and applications are transformed, decomposed and delegated until they are finally executed by hardware devices. However, most works do not describe the final execution phase, when a certain device is selected to perform an action. Therefore, in this paper we describe a management solution to coordinate the execution of low-level services in CPS. The solution employs a probabilistic selection technique based on the concept of Cost and Quality-of-Service, and includes both an orchestration algorithm and a choreography procedure. The proposal includes, moreover, a general framework explaining all the management levels and an experimental validation which evaluates the performance of the proposed technology.

Improving MOOC Student Learning Through Enhanced Peer-to-Peer Tasks

In the context of MOOCs, activities that imply a deeper learning are, undoubtedly, P2P tasks. However, the traditional MOOC structure makes very difficult to evaluate the learning level obtained by students when performing these activities. This situation is especially problematic as students increasingly demand the universities to certify the knowledge acquired by means of MOOCs, so higher education institutions must guarantee their learning. In order to address this challenge, in this paper it is proposed a new type of P2P activity, designed to automatically provide students a valuable feedback about their work. This new type of activity is supported by a module, including a coordination engine and a formal revision component communicating by means of the LTI protocol with an automatic revision assistant, which allows differentiating a genuine contribution from the simple repetition of ideas. Moreover, and experimental validation is carried out. Results show first evidences that most students (up to 82%) improve their learning when employed the new proposed technology.