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Thesis
Home / Post Doctorat / Detection of cyber-attacks in a smart multi-sensor embedded system for soil monitoring
Detection of cyber-attacks in a smart multi-sensor embedded system for soil monitoring
Computer science and softwareEngineering sciencesMathematics - Numerical analysis - Simulation
Abstract
The post-doc is concerned with the application of machine learning methods to detect potential cyber-security attacks on a connected multi-sensor system. The application domain is the agriculture, where CEA Leti has several projects, among which the H2020 project SARMENTI (Smart multi-sensor embedded and secure system for soil nutrient and gaseous emission monitoring). The objective of SARMENTI is to develop and validate a secure, low power multisensor systems connected to the cloud to make in situ soil nutrients analysis and to provide decision support to the farmers by monitoring soil fertility in real-time. Within this topic, the postdoc is concerned with the cyber-security analysis to determine main risks in our multi-sensor case and with the investigation of a attack detection module. The underlying detection algorithm will be based on anomaly detection, e.g., one-class classifier. The work has tree parts, implement the probes that monitor selected events, the communication infrastructure that connects the probes with the detector, and the detector itself.
Laboratory
Département Architectures Conception et Logiciels Embarqués (LIST-LETI)
Service Calcul et Systèmes Numériques
Laboratoire Infrastructure et Ateliers Logiciels pour Puces