Name
Abstract | ||
|---|---|---|
Smart connected devices create what has been denominated as the Internet of Things (IoT). The combined and cohesive use of these devices prompts the emergence of Ambient Intelligence (AmI). One of the current key issues in the IoT domain has to do with the detection and prevention of security breaches and intrusions. In this paper, we introduce the use of the Voronoi diagram-based Evolutionary Algorithm (VorEAl) in the context of IoT intrusion detection. In order to cope with the dimensions of the problem, we propose a modification of VorEAl that employs a proxy for the volume that approximates it using a heuristic surrogate. The proxy has linear complexity and, therefore, highly scalable. The experimental studies carried out as part of the paper show that our approach is able to outperform other approaches that have been previously used to address the problem of interest. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-92639-1_30 | HYBRID ARTIFICIAL INTELLIGENT SYSTEMS (HAIS 2018) |
Keywords | Field | DocType |
IDS, IoT, Machine learning, Predictive analysis, Time series | Heuristic,Evolutionary algorithm,Computer science,Ambient intelligence,Internet of Things,Voronoi diagram,Artificial intelligence,Linear complexity,Intrusion detection system,Machine learning,Scalability,Distributed computing | Conference |
Volume | ISSN | Citations |
10870 | 0302-9743 | 1 |
PageRank | References | Authors |
0.34 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nayat Sánchez Pi | 1 | 48 | 15.93 |
| Luis Martí | 2 | 43 | 9.51 |
| José M. Molina | 3 | 604 | 67.82 |