The Cost of Trust in the Dynamics of Best Attachment

The need of trust is growing in several contexts as e-commerce, virtual communities, distributed on-line services and many others as an essential precautionary component for users during interactions with strangers, either other people or virtual agents. Generally trust metrics endorse the principle "the higher the trust, the more legitimate that user will be''; a consequence is that getting trusted must require some effort, otherwise all participants would easily achieve high trustworthiness. In this work we study how a user can achieve and preserve a good trust and what costs it requires over time; we also investigate some heuristics that allow reducing the complexity in exploring the rank-effort space especially for large networks

Network robustness improvement via long-range links

Abstract Many systems are today modelled as complex networks, since this representation has been proven being an effective approach for understanding and controlling many real-world phenomena. A significant area of interest and research is that of networks robustness, which aims to explore to what extent a network keeps working when failures occur in its structure and how disruptions can be avoided. In this paper, we introduce the idea of exploiting long-range links to improve the robustness of Scale-Free (SF) networks. Several experiments are carried out by attacking the networks before and after the addition of links between the farthest nodes, and the results show that this approach effectively improves the SF network correct functionalities better than other commonly used strategies

An Intelligent and Pervasive Surveillance System for Home Security

Domotics is a promising area for intelligent and pervasive applications that aims at achieving a better quality of life. Harnessing modern technologies is valuable in many contexts, in particular in home surveillance scenario, where people safety or security might be threatened. Modern home security systems endorse monitoring as well as control functions in a remote fashion, e.g. via devices as a laptops, PDAs, or cell phones, thus implementing the pervasive computing paradigma; moreover, the intelligence is now often embedded into modern applications, e.g. surveillance systems could adapt to the environment through a self-learning algorithm. This work presents an intelligent and pervasive surveillance system for home and corporate security based on the ZigBee protocol which detects and classifies intrusions discarding false positives, also providing remote control and cameras live streaming. Results of tests in different environments show the effectiveness of the proposed system

virtualization for effective risk free network security assessment

Computer networks security is a hard issue, which continuously evolves due to the change of technologies, architectures and algorithms and the growing complexity of architectures and systems. This question is enforced in distributed contexts where the lack of a central authority imposes to set up a proper strategy for both passive and active security. Moreover, it is also essential to test the strategy under as many attack scenarios as possible, to discover and tackle unforeseen situations; this cannot be easily performed on the real system without avoiding either security risks (when it is running) or high costs (if the system must be disconnected from the network during tests). A viable solution is represented by the use of virtualization technologies. Leveraging virtualization permits us to set up an effective and efficient real network duplicate, which can be used for the assessment of security in a non-trivial, risk-free and costs saving fashion

Multisource agent-based healthcare data gathering

The number and type of digital sources storing healthcare data is increasing more and more, rising the problem of collecting actually dispersed information about a single patient. In this paper we propose an agent-based system to support integration of health-related data extracted from both structured (HIS) and semi-structured (websites and social networks) sources. Integrated data are exported in HL7 format to finally feed personal health record (PHR)

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 efficient real-time architecture for collecting IoT data

IoT applications has some characteristics that set it apart from other fields mainly due to the multitude of different types of sensors producing data. In monitoring applications, data processing requires real-time or soft real-time responses in order to aid systems to make important decisions but also predictive analysis to leverage the potential of IoT by data mining vast datasets. This paper presents an architecture developed to efficiently process and store data coming from an huge number of distributed IoT sensors. The back-end of SeeYourBox services is currently based on the proposed architecture that has proven to be stable and meet all the requirements