Preventive Security for IoT

We are using advanced mathematical models for machine learning dedicated to high IoT traffic analytics. We are working with artificial intelligence Research scientist (IRIDIA) for improving anomaly detection algorithm on IoT patterns. Combined with Degetel expertise in IoT and Big Data expertise.

Anomaly Detection on high IoT traffic

Phileas give you access to last academic research on IoT behaviours analytics with Machine Learning. Severals mathematical models are adapted and tuned for IoT behaviours, forming a framework of good practice knowledge.

  • Neural networks
    • Autoencoders
    • Long short-term memory
  • Distance based algorithms
    • Local Outlier Factor
    • Clustering
  • Time Series
    • Probabilistic exponentially weighted moving average.

Who are we?

Philéas is part of the TeamUP 2017 Innoviris program, aimed at fostering the synergy between research and development in Artificial Intelligence and the cooperation between the academic and the industrial sector.

The ULB Artificial Intelligence Laboratory is oriented towards themes of biological inspiration such as complex systems and swarm intelligence in optimisation and robotics, but also in machine learning and data mining.

Consulting firm specialized in innovation and digital expertise. Degetel has a 9 years experience in networks management for connected objects and Big Data.

Data Exploration with Phileas