Exploring social relations for the intrusion detection in ad hoc networks

The explosive growth of the Internet, the emergence of social networks and recent technological advances enabled an enormous user population to become actuators in this new emerging cultural environment. Handheld wireless devices, like smartphones and tablets, which can be internet-connected, allow users to join the Internet community from any place at any time. Users are of various and diverse cultural profiles. Social networks form a modern global environment where all these users can actually become cultural actuators in the sense that they socialize, communicate, announce and reproduce information promoting local, national and international activities closely related to their cultural background. Modern social networks, like Facebook or Twitter, form active and vivid channels of cultural information circulation. Thousands of single users or user groups make frequent announcements about special cultural events, related to music, dance, theater, cinema, gastronomy, performances, exhibitions, gatherings of a special cultural character. In addition, such announcements made in the form of short, inclusive posts bear unique online features so that their audience can immediately exploit them. However, it remains an important challenge to efficiently mine useful data from such populated, diverse and vaguely structured spaces. Motivated by the case of Santorini Island, Greece and a strong recent observation that local traditional activities or special (multi-)cultural events and activities tend to be absent from touristic guides and plans, we present a WordPress-based website which automatically collects cultural data from Facebook and presents it in a comprehensive way for promoting cultural activity in Santorini. Lack of information implies lack of knowledge which consequently results in a reduced interest and decision space. Utilizing keywords spanning a variety of cultural activities and events, our system serves as an aggregator for Facebook posts of particular cultural interest. While several, mainly not collaborating, entities-like for instance Facebook users or groups, websites, Twitter users or groups-do release this sort of information, lack of organization and timely viewing makes it extremely inefficient for interested entities to locate, evaluate and exploit this highly distributed and unstructured material. The experimental use of our system so far-as an application offered from the Department of Cultural Heritage Management and New Technologies of the University of Patras-shows that technology can indeed serve an important role towards efficient cultural management and fruitful intercultural cooperation.

show abstract

Exploring social relations for the intrusion detection in ad hoc networks

Cited by 2 publications

References 22 publications

A Network Intrusion Detection Method Based on Deep Multi-scale Convolutional Neural Network

A Network Intrusion Detection Method Based on Deep Multi-scale Convolutional Neural Network

Data Mining Prospects in Mobile Social Networks

Contact Info

Product

Resources

About