Tackling Threatening behavior through a Semantic Approach - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2022

Tackling Threatening behavior through a Semantic Approach

Résumé

We introduce a new approach to characterize and detect threatening behaviors in surveillance systems, without relying on history or expertise. This approach consists in simulating the worst-case attack plans, fusing their semantic descriptions and using the produced patterns to raise alerts in operational conditions. We demonstrate our set of tools on a simple scenario involving geolocated sensors looking for moving vehicles targeting a protected objective. We find that the system is able to recover well-grounded graph patterns defining detection rules which make sense in the operational context. We believe that our approach achieves a relevant compromise between data-based and expertise-based systems, and allows for a good balance between efficiency and understandability.
Fichier principal
Vignette du fichier
2022_Laudy-Fossier-Dreo__Tackling_abnormal_behaviour_through_a_semantic_approach.pdf (2.67 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04128705 , version 1 (14-06-2023)

Identifiants

Citer

Claire Laudy, Simon Fossier, Johann Dreo. Tackling Threatening behavior through a Semantic Approach. 25th International Conference on Information Fusion (FUSION), International Society of Information Fusion, Jul 2022, Linköping, Sweden. ⟨10.23919/FUSION49751.2022.9841333⟩. ⟨hal-04128705⟩

Collections

PASTEUR
10 Consultations
18 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More