Luca Brilli
University of Florence
8 Papers
24 Citations
Luca Brilli is an academic researcher from University of Florence. The author has contributed to research in topics: Quality of experience & Security information and event management. The author has an hindex of 4, co-authored 8 publications.
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Papers
The Role of Physical Layer Security in IoT: A Novel Perspective
TL;DR: The IoT threats are analyzed, a security framework for the device initialization is proposed and it is shown how physical layer security can effectively boost the security of IoT systems.
Physical Layer Security for IoT Devices Configuration and Key Management - a Proof of Concept
Luca Brilli,Tommaso Pecorella,Lorenzo Mucchi +2 more
- 01 Jan 2016
TL;DR: This work proposes a method that leverages the physical layer security to establish a secure channel which allows a secure exchange of cryptographic keys, enhancing the security while maintaining a very low management overhead, i.e., with minimal interference on the normal user workflow.
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Physical layer security for IoT devices configuration and key management - a Proof of Concept
Luca Brilli,Tommaso Pecorella,Lorenzo Mucchi +2 more
- 01 Jan 2016
TL;DR: In this paper, the authors propose a method that leverages the physical layer security to establish a secure channel which allows a secure exchange of cryptographic keys, enhancing the security while maintaining a very low management overhead.
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The Effect of Video Caching on Network Resource Planning - A Real-Case Study
Luca Brilli,Romano Fantacci,Tommaso Pecorella,Tiziano Ionta +3 more
- 01 Jan 2016
TL;DR: Traffic Engineering is one of the building blocks for a correct network planning and helps Internet Service Providers fulfill the user Quality of Experience (QoE).
Enhance the QoE for smartphone applications: An API approach for QoS control in LTE-A
Roberto Viti,Tommaso Pecorella,Luca Brilli,Romano Fantacci,Camillo Carlini +4 more
- 01 Oct 2015
TL;DR: A novel architecture to address the problem of application Quality of Experience (QoE) management for rapidly evolving and heterogeneous network scenarios is proposed and can be used for mixed Long Term Evolution Advanced and Wi-Fi systems.
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