Search

This paper proposes a prediction model based on fuzzy logic applied to anticipate electricity production and consumption in a building equipped with photovoltaics and connected to the grid. The goal is a smart energy management system able to make decisions and to adapt the consumption to the actual context and to the future electricity levels. The interest is to use as much electricity as possible from own production. The surplus is captured by an energy storage system or is sent to the grid. When no electricity is available from self‐production, the grid is used to cover the necessities. The evaluations are performed on a data set collected in a real household. The proposed method is compared in terms of mean absolute error with other existing methods. The method developed based on fuzzy logic has an error of about 67 W, which places it among the most efficient models. [ABSTRACT FROM AUTHOR]

Modern interconnected power grids are a critical target of many kinds of cyber‐attacks, potentially affecting public safety and introducing significant economic damages. In such a scenario, more effective detection and early alerting tools are needed. This study introduces a novel anomaly detection architecture, empowered by modern machine learning techniques and specifically targeted for power control systems. It is based on stacked deep neural networks, which have proven to be capable to timely identify and classify attacks, by autonomously eliciting knowledge about them. The proposed architecture leverages automatically extracted spatial and temporal dependency relations to mine meaningful insights from data coming from the target power systems, that can be used as new features for classifying attacks. It has proven to achieve very high performance when applied to real scenarios by outperforming state‐of‐the‐art available approaches. [ABSTRACT FROM AUTHOR]

The more recent advances in network communication and cloud computing technologies have the potential of significantly improving traveling experience by providing value-added services, such as multimedia on demand (MoD), in vehicular ad hoc networks, where the involved vehicles are provided with enough communication, storage, and computing capabilities. In this scenario, despite many consolidated mobile cloud solutions and pay-per-view systems have been developed and widely deployed in public transportation, the security and privacy of mobile users, mainly concerning the association between users' identities and requested multimedia contents, still presents several open challenges. Mainly, providing pay-per-view services in vehicular clouds while protecting the passenger's anonymity and simultaneously ensuring the robustness of the payment system has become an important issue.Accordingly, we present a novel smart card-based MoD payment solution, to be used in mobile cloud-empowered public transportation systems, that not only guarantees the passenger's anonymity but also uses a personal trusted device to protect the passenger's sensitive information so that he can enjoy the multimedia contents during the long hours of travel. In the future, such scheme can become common practice on MoD-related equipment in vehicular ad hoc networks, thereby enhancing the competitiveness of public transport companies. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The provision of efficient broadcast containment schemes that can dynamically cope with frequent topology changes and limited shared channel bandwidth, is one of the most challenging research topics in MANETs, and is crucial to the basic operations of networks serving fully mobile devices within areas having no fixed communication infrastructure. This problem particularly impacts the design of dynamic routing protocol that can efficiently establish routes to deliver data packets among mobile nodes with minimum communication overhead, and at the same time, ensure high throughput and low end-to-end delay. Accordingly, this work exploits and analyzes an adaptive probabilistic broadcast containment technique based on a particular condensation phenomenon borrowed from Quantum Mechanics and transposed in self-organizing random networks, that has the potential to effectively drive the on-demand route discovery process. Simulation-based performance analysis has shown that the proposed technique can introduce significant benefits on the general performance of broadcast-based reactive routing protocols in MANETs. [ABSTRACT FROM AUTHOR]

Wireless networks are more and more popular in our life, but their increasing pervasiveness and widespread coverage raises serious security concerns. Mobile client devices potentially migrate, usually passing through very light access control policies, between numerous and heterogeneous wireless environments, bringing with them software vulnerabilities as well as possibly malicious code. To cope with these new security threats the paper proposes a new active third party authentication, authorization and security assessment strategy in which, once a device enters a new Wi-Fi environment, it is subjected to analysis by the infrastructure, and if it is found to be dangerously insecure, it is immediately taken out from the network and denied further access until its vulnerabilities have been fixed. The security assessment module, that is the fundamental component of the aforementioned strategy, takes advantage from a reliable knowledge base containing semantically-rich information about the mobile node under examination, dynamically provided by network mapping and configuration assessment facilities. It implements a fully automatic security analysis framework, based on AHP, which has been conceived to be flexible and customizable, to provide automated support for real-time execution of complex security/risk evaluation tasks which depends on the results obtained from different kind of analysis tools and methodologies. Encouraging results have been achieved utilizing a proof-of-concept model based on current technology and standard open-source networking tools. [ABSTRACT FROM AUTHOR]