Enabling Risk Management for Smart Infrastructures with an Anomaly Behavior Analysis Intrusion Detection System - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2017

Enabling Risk Management for Smart Infrastructures with an Anomaly Behavior Analysis Intrusion Detection System

Xiaoyang Zhu
Youakim Badr

Résumé

Abstract: The Internet of Things (IoT) connects not only computers and mobile devices, but it also interconnects smart buildings, homes, and cities, as well as electrical grids, gas, and water networks, automobiles, airplanes, etc. However, IoT applications introduce grand security challenges due to the increase in the attack surface. Current security approaches do not handle cybersecurity from a holistic point of view; hence a systematic cybersecurity mechanism needs to be adopted when designing IoTbased applications. In this work, we present a risk management framework to deploy secure IoT-based applications for Smart Infrastructures at the design time and the runtime. At the design time, we propose a risk management method that is appropriate for smart infrastructures. At the design time, our framework relies on the Anomaly Behavior Analysis (ABA) methodology enabled by the Autonomic Computing paradigm and an intrusion detection system to detect any threat that can compromise IoT infrastructures by. Our preliminary experimental results show that our framework can be used to detect threats and protect IoT premises and services.
Fichier non déposé

Dates et versions

hal-01619366 , version 1 (19-10-2017)

Identifiants

  • HAL Id : hal-01619366 , version 1

Citer

Jesus Pacheco, Xiaoyang Zhu, Youakim Badr, Salim Hariri. Enabling Risk Management for Smart Infrastructures with an Anomaly Behavior Analysis Intrusion Detection System. IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W), Sep 2017, Tuscon, United States. pp.324 - 328. ⟨hal-01619366⟩
549 Consultations
0 Téléchargements

Partager

Gmail Facebook X LinkedIn More