Published May 15, 2023 | Version v1
Conference paper Open

Runtime security monitoring by an interplay between rule matching and deep learning-based anomaly detection on logs

Creators

  • 1. XLAB
  • 2. Tecnalia
  • 3. Alexandra Lakka Synelixis
  • 4. Prodevelop

Description

In the era of digital transformation, the increasing vulnerability of infrastructure and applications is often tied to the lack of technical capability and the improved intelligence of attackers. In this paper, we discuss the complementarity between static security monitoring of rule matching and an application of self-supervised machine learning to cybersecurity. Moreover, we analyze the context and challenges of supply chain resilience and smart logistics. Furthermore, we put this interplay between the two complementary methods in the context of a self-learning and self-healing approach.

Files

Paper IOSEC 2023.pdf

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Additional details

Funding

European Commission
FISHY – A coordinated framework for cyber resilient supply chain systems over complex ICT infrastructures 952644
European Commission
MEDINA – Security framework to achieve a continuous audit-based certificationn in compliance with the EU-wide cloud security certification scheme 952633
European Commission
PIACERE – Programming trustworthy Infrastructure As Code in a sEcuRE framework 101000162