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Authors: Csongor Tamás 1 ; 2 ; Dorottya Papp 1 and Levente Buttyán 1

Affiliations: 1 Laboratory of Cryptography and System Security (CrySyS Lab), Department of Networked Systems and Services, Budapest University of Technology and Economics, Hungary ; 2 Ukatemi Technologies, Hungary

Keyword(s): IoT, Embedded Systems, Malware Detection, Binary Similarity, Locality Sensitive Hashing.

Abstract: Embedded devices connected to the Internet are threatened by malware, and currently, no antivirus product is available for them. We present SIMBIoTA, a new approach for detecting malware on such IoT devices. SIMBIoTA relies on similarity-based malware detection, and it has a number of notable advantages: moderate storage requirements on resource constrained IoT devices, a fast and lightweight malware detection process, and a surprisingly good detection performance, even for new, never-before-seen malware. These features make SIMBIoTA a viable antivirus solution for IoT devices, with competitive detection performance and limited resource requirements.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Tamás, C.; Papp, D. and Buttyán, L. (2021). SIMBIoTA: Similarity-based Malware Detection on IoT Devices. In Proceedings of the 6th International Conference on Internet of Things, Big Data and Security - IoTBDS; ISBN 978-989-758-504-3; ISSN 2184-4976, SciTePress, pages 58-69. DOI: 10.5220/0010441500580069

@conference{iotbds21,
author={Csongor Tamás. and Dorottya Papp. and Levente Buttyán.},
title={SIMBIoTA: Similarity-based Malware Detection on IoT Devices},
booktitle={Proceedings of the 6th International Conference on Internet of Things, Big Data and Security - IoTBDS},
year={2021},
pages={58-69},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010441500580069},
isbn={978-989-758-504-3},
issn={2184-4976},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Internet of Things, Big Data and Security - IoTBDS
TI - SIMBIoTA: Similarity-based Malware Detection on IoT Devices
SN - 978-989-758-504-3
IS - 2184-4976
AU - Tamás, C.
AU - Papp, D.
AU - Buttyán, L.
PY - 2021
SP - 58
EP - 69
DO - 10.5220/0010441500580069
PB - SciTePress