Visible to the public Enabling Risk Management for Smart Infrastructures with an Anomaly Behavior Analysis Intrusion Detection System

TitleEnabling Risk Management for Smart Infrastructures with an Anomaly Behavior Analysis Intrusion Detection System
Publication TypeConference Paper
Year of Publication2017
AuthorsPacheco, J., Zhu, X., Badr, Y., Hariri, S.
Conference Name2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W)
Date PublishedSept. 2017
PublisherIEEE
ISBN Number978-1-5090-6558-5
KeywordsABA methodology, anomaly behavior analysis, Anomaly Behavior Analysis methodology, Autonomic computing, Autonomic Security, Computational modeling, computer security, cyber security, cybersecurity mechanism, Internet of Things, Intrusion detection, intrusion detection system, intrusion tolerance, IoT, IoT infrastructures security, Metrics, mobile computing, mobile devices, pubcrawl, Resiliency, risk management, risk management framework, risk management method, Scalability, security of data, Sensors, smart infrastructures, software fault tolerance, threat model
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.

URLhttps://ieeexplore.ieee.org/document/8064143
DOI10.1109/FAS-W.2017.167
Citation Keypacheco_enabling_2017