Enabling Risk Management for Smart Infrastructures with an Anomaly Behavior Analysis Intrusion Detection System
Title | Enabling Risk Management for Smart Infrastructures with an Anomaly Behavior Analysis Intrusion Detection System |
Publication Type | Conference Paper |
Year of Publication | 2017 |
Authors | Pacheco, J., Zhu, X., Badr, Y., Hariri, S. |
Conference Name | 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W) |
Date Published | Sept. 2017 |
Publisher | IEEE |
ISBN Number | 978-1-5090-6558-5 |
Keywords | ABA 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. |
URL | https://ieeexplore.ieee.org/document/8064143 |
DOI | 10.1109/FAS-W.2017.167 |
Citation Key | pacheco_enabling_2017 |
- IoT infrastructures security
- threat model
- software fault tolerance
- smart infrastructures
- sensors
- security of data
- Scalability
- risk management method
- risk management framework
- risk management
- Resiliency
- pubcrawl
- mobile devices
- mobile computing
- Metrics
- ABA methodology
- IoT
- intrusion tolerance
- intrusion detection system
- Intrusion Detection
- Internet of Things
- cybersecurity mechanism
- cyber security
- computer security
- Computational modeling
- Autonomic Security
- Autonomic computing
- Anomaly Behavior Analysis methodology
- anomaly behavior analysis