Placement optimization of IoT security solutions for edge computing based on graph theory
| Title | Placement optimization of IoT security solutions for edge computing based on graph theory |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Godquin, Tanguy, Barbier, Morgan, Gaber, Chrystel, Grimault, Jean-Luc, Bars, Jean-Marie Le |
| Conference Name | 2019 IEEE 38th International Performance Computing and Communications Conference (IPCCC) |
| Date Published | Oct. 2019 |
| Publisher | IEEE |
| ISBN Number | 978-1-7281-1025-7 |
| Keywords | Centrality, centrality metrics, computer network security, Computing Theory, cryptography, dominating set, edge computing, edge computing security, EndToEnd like encryption, graph theory, Internet of Things, IoT, IoT network, IoT security framework, IoT security solutions, Metrics, placement optimization, pubcrawl, security as a service, security functions, security metrics |
| Abstract | In this paper, we propose a new method for optimizing the deployment of security solutions within an IoT network. Our approach uses dominating sets and centrality metrics to propose an IoT security framework where security functions are optimally deployed among devices. An example of such a solution is presented based on EndToEnd like encryption. The results reveal overall increased security within the network with minimal impact on the traffic. |
| URL | https://ieeexplore.ieee.org/document/8958767 |
| DOI | 10.1109/IPCCC47392.2019.8958767 |
| Citation Key | godquin_placement_2019 |
- Internet of Things
- Security Metrics
- security functions
- security as a service
- pubcrawl
- placement optimization
- Metrics
- IoT security solutions
- IoT security framework
- IoT network
- IoT
- Centrality
- graph theory
- EndToEnd like encryption
- edge computing security
- edge computing
- dominating set
- Cryptography
- Computing Theory
- computer network security
- centrality metrics