HADES-IoT: A practical host-based anomaly detection system for IoT devices (Extended Version)

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F22%3APU139566" target="_blank" >RIV/00216305:26230/22:PU139566 - isvavai.cz</a>

Result on the web

<a href="https://arxiv.org/abs/1905.01027" target="_blank" >https://arxiv.org/abs/1905.01027</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/JIOT.2021.3135789" target="_blank" >10.1109/JIOT.2021.3135789</a>

Result language

angličtina

Original language name

HADES-IoT: A practical host-based anomaly detection system for IoT devices (Extended Version)

Original language description

Internet of Things (IoT) devices have become ubiquitous and are spread across many application domains including the industry, transportation, healthcare, and households. However, the proliferation of the IoT devices has raised the concerns about their security, especially when observing that many manufacturers focus only on the core functionality of their products due to short time to market and low-cost pressures, while neglecting security aspects. Moreover, it does not exist any established or standardized method for measuring and ensuring the security of IoT devices. Consequently, vulnerabilities are left untreated, allowing attackers to exploit IoT devices for various purposes, such as compromising privacy, recruiting devices into a botnet, or misusing devices to perform cryptocurrency mining. In this paper, we present a practical Host-based Anomaly DEtection System for IoT (HADES-IoT) that represents the last line of defense. HADES-IoT has proactive detection capabilities, provides tamper-proof resistance, and it can be deployed on a wide range of Linux-based IoT devices. The main advantage of HADES-IoT is its low performance overhead, which makes it suitable for the IoT domain, where state-of-the-art approaches cannot be applied due to their high-performance demands. We deployed HADES-IoT on seven IoT devices to evaluate its effectiveness and performance overhead. Our experiments show that HADES-IoT achieved 100% effectiveness in the detection of current IoT malware such as VPNFilter and IoTReaper; while on average, requiring only 5.5% of available memory and causing only a low CPU load.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/8A19010" target="_blank" >8A19010: Arrowhead Tools for Engineering of Digitalisation Solutions</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

IEEE Internet of Things Journal

ISSN

2327-4662

e-ISSN

—

Volume of the periodical

9

Issue of the periodical within the volume

12

Country of publishing house

US - UNITED STATES

Number of pages

19

Pages from-to

9640-9658

UT code for WoS article

000808096100047

EID of the result in the Scopus database

2-s2.0-85121823034