Zobrazeno 1 - 10
of 161
pro vyhledávání: '"Bennati, Stefano"'
Collective privacy loss becomes a colossal problem, an emergency for personal freedoms and democracy. But, are we prepared to handle personal data as scarce resource and collectively share data under the doctrine: as little as possible, as much as ne
Externí odkaz:
http://arxiv.org/abs/2301.05995
Mobility patterns of vehicles and people provide powerful data sources for location-based services such as fleet optimization and traffic flow analysis. Location-based service providers must balance the value they extract from trajectory data with pr
Externí odkaz:
http://arxiv.org/abs/2011.09218
Publikováno v:
In Structures December 2023 58
Publikováno v:
In Structures December 2023 58
Several smart city services rely on users contribution, e.g., data, which can be costly for the users in terms of privacy. High costs lead to reduced user participation, which undermine the success of smart city technologies. This work develops a sce
Externí odkaz:
http://arxiv.org/abs/1805.09090
The effect of phenotypic plasticity on evolution, the so-called Baldwin effect, has been studied extensively for more than 100 years. Plasticity is known to influence the speed of evolution towards a specific genetic configuration, but whether it als
Externí odkaz:
http://arxiv.org/abs/1710.00352
Autor:
Bennati, Stefano, Jonker, Catholijn M.
This paper introduces PriMaL, a general PRIvacy-preserving MAchine-Learning method for reducing the privacy cost of information transmitted through a network. Distributed sensor networks are often used for automated classification and detection of ab
Externí odkaz:
http://arxiv.org/abs/1703.07150
Autor:
Bennati, Stefano, Pournaras, Evangelos
Big data collection practices using Internet of Things (IoT) pervasive technologies are often privacy-intrusive and result in surveillance, profiling, and discriminatory actions over citizens that in turn undermine the participation of citizens to th
Externí odkaz:
http://arxiv.org/abs/1702.08817
Autor:
Bennati, Stefano
Collective sensing is an emergent phenomenon which enables individuals to estimate a hidden property of the environment through the observation of social interactions. Previous work on collective sensing shows that gregarious individuals obtain an ev
Externí odkaz:
http://arxiv.org/abs/1602.06737
Autor:
Nunes, Eric, Buto, Casey, Shakarian, Paulo, Lebiere, Christian, Bennati, Stefano, Thomson, Robert, Jaenisch, Holger
Identifying the tasks a given piece of malware was designed to perform (e.g. logging keystrokes, recording video, establishing remote access, etc.) is a difficult and time-consuming operation that is largely human-driven in practice. In this paper, w
Externí odkaz:
http://arxiv.org/abs/1507.01930