Modern cars include a huge number of sensors and actuators, which continuously exchange data and control commands. The most used protocol for communication of different components in automotive system is the Controller Area Network (CAN). According to CAN, components communicate by broadcasting messages on a bus. In addition, the standard definition of the protocol does not provide information for authentication, so exposing it to attacks. This paper proposes a method based on deep learning aiming at discovering attacks towards the CAN-bus. In particular, Neural Networks and MultiLayer Perceptrons are the class of networks employed in our approach. We also validate our approach by analysing a real-world dataset with the injection of messages from different types of attacks: denial of service, fuzzy pattern attacks, and attacks against specific components. The obtained results are encouraging and demonstrate the effectiveness of the approach.

In this paper, we present an ongoing project, named Talking Museum and developed within DATABENC - a high technology district for Cultural Heritage management. The project exploits the Internet of Things technologies in order to make objects of a museum exhibition able to “talk” during users’ visit and capable of automatically telling their story using multimedia facilities. In particular, we have deployed in the museum a particular Wireless Sensor Network that, using Bluetooth technology, is able to sense the surrounding area for detecting user devices’ presence. Once a device has been detected, the related MAC address is retrieved and a multimedia story of the closest museum objects is delivered to the related user. Eventually, proper multimedia recommendation techniques drive users towards other objects of possible interest to facilitate and make more stimulating the visit. As case of study, we show an example of Talking museum as a smart guide of sculptures’ art exhibition within the Maschio Angioino castle, in Naples (Italy)

Information and Communication Technologies have radically changed the modern Cultural Heritage scenery: Simple traditional Information Systems supporting the management of cultural artifacts have left the place to complex systems that expose rich information extracted from heterogeneous data sources—like Sensor Networks, Social Networks, Digital Libraries, Multimedia Collections, Web Data Service, and so on—by means of sophisticated applications that enhance the users’ experience. In this article, we describe SCRABS, a Smart Context-awaRe Browsing assistant for cultural EnvironmentS . SCRABS has been developed during the Cultural Heritage Information Systems national project and promoted by DATABENC, the Cultural Heritage Technological District of the Campania Region, in Italy. SCRABS has been designed on top of a Big Data technological stack as the result of a multidisciplinary project carried out by a heterogeneous team of computer scientists, archeologists, architects, and experts in humanities. We describe the main ideas that support the system, showing its use in some real application scenarios located in the Paestum Archeologica Sites.

In this paper, we describe the project SNOPS, a smart-city environment based on Future Internet technologies. We fo- cused on the context-aware recommendation services pro- vided in the platform, which accommodates location depen- dent multimedia information with user's needs in a mobile environment related to an outdoor scenario within the Cul- tural Heritage domain. In particular, we describe a recom- mendation strategy for planning browsing activities exploit- ing objects features, users' behaviors and context informa- tion gathered by apposite sensor networks. Preliminary ex- perimental results, related to user's satisfaction, have been carried out and discussed