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Authors: Valerio Selis and Alan Marshall

Affiliation: University of Liverpool, United Kingdom

Keyword(s): IoT, M2M, Trust, Embedded Systems, Virtual Machines.

Related Ontology Subjects/Areas/Topics: Data and Application Security and Privacy ; Information and Systems Security ; Trust Management and Reputation Systems

Abstract: Security in the Internet of Things (IoT) is now considered a priority, and trust in machine-to-machine (M2M) communications is expected to play a key role. This paper presents a mechanism to detect an emerging threat in M2M systems whereby an attacker may create multiple fake embedded machines using virtualized or emulated systems, in order to compromise either a targeted IoT device, or the M2M network. A new trust method is presented that is based on a characterisation of the behaviours of real embedded machines, and operates independently of their architectures and operating systems, in order to detect virtual and emulated systems. A range of tests designed to characterise embedded and virtual devices are presented, and the results underline the efficiency of the proposed solution for detecting these systems easily and quickly.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Selis, V. and Marshall, A. (2015). MEDA: A Machine Emulation Detection Algorithm. In Proceedings of the 12th International Conference on Security and Cryptography (ICETE 2015) - SECRYPT; ISBN 978-989-758-117-5; ISSN 2184-3236, SciTePress, pages 228-235. DOI: 10.5220/0005535202280235

@conference{secrypt15,
author={Valerio Selis. and Alan Marshall.},
title={MEDA: A Machine Emulation Detection Algorithm},
booktitle={Proceedings of the 12th International Conference on Security and Cryptography (ICETE 2015) - SECRYPT},
year={2015},
pages={228-235},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005535202280235},
isbn={978-989-758-117-5},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Security and Cryptography (ICETE 2015) - SECRYPT
TI - MEDA: A Machine Emulation Detection Algorithm
SN - 978-989-758-117-5
IS - 2184-3236
AU - Selis, V.
AU - Marshall, A.
PY - 2015
SP - 228
EP - 235
DO - 10.5220/0005535202280235
PB - SciTePress