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ThinkMind // CENICS 2017, The Tenth International Conference on Advances in Circuits, Electronics and Micro-electronics // View article cenics_2017_4_30_68005


Anomaly-Based Intrusion Detection System for Embedded Devices on Internet

Authors:
Deepak Mehta
Alie El-Din Mady
Menouer Boubekeur
Devu Manikantan Shila

Keywords: Securityl Embedded devices, Internet of Things, Intrusion Detection

Abstract:
Embedded devices connected to the Internet ranging from garage door openers, home thermostats, home automation systems to automobiles, are continuously exploited by remote attack vectors. According to OWASP Internet of Things project, these vulnerabilities are due to insecure web interfaces, insufficient authentication and authorization, insufficient transport layer protection, broken cryptography, insecure software/firmware updates, or poor physical security. As opposed to PowerPC systems, embedded devices lack resources to run advanced attack detection or anti-virus softwares. Moreover, embedded devices are often mass produced (thousand to millions) and share a static security footprint. Hence, a successful attack on a single device can be replicated across other devices with minimal effort. There exists a significant need towards developing a resilient cyber security methodology that provides scalable and efficient intrusion detection and resilient architecture. In this paper, we present an efficient hierarchical anomaly-based intrusion detection method and resilient policy framework that enables the system to detect any suspicious activity and continue the operation with minimum functionality.

Pages: 65 to 69

Copyright: Copyright (c) IARIA, 2017

Publication date: September 10, 2017

Published in: conference

ISSN: 2308-426X

ISBN: 978-1-61208-585-2

Location: Rome, Italy

Dates: from September 10, 2017 to September 14, 2017

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