ChronoEOS 2.0: Device Fingerprinting and EOSIO Blockchain Technology for On-Running Forensic Analysis in an IoT Environment
In industrial environments there are critical devices, so their correct operation must be ensured. In particular, having a secure record of the different events related to these devices is essential. Thus, this record can be used in future forensic investigations in case of accidents or production f...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-03-01
|
Series: | Smart Cities |
Subjects: | |
Online Access: | https://www.mdpi.com/2624-6511/6/2/43 |
_version_ | 1797603438681391104 |
---|---|
author | José Álvaro Fernández-Carrasco Xabier Echeberria-Barrio Daniel Paredes-García Francesco Zola Raul Orduna-Urrutia |
author_facet | José Álvaro Fernández-Carrasco Xabier Echeberria-Barrio Daniel Paredes-García Francesco Zola Raul Orduna-Urrutia |
author_sort | José Álvaro Fernández-Carrasco |
collection | DOAJ |
description | In industrial environments there are critical devices, so their correct operation must be ensured. In particular, having a secure record of the different events related to these devices is essential. Thus, this record can be used in future forensic investigations in case of accidents or production failures. In this sense, blockchain technology can bring reliability to the event log. In this paper, ChronoEOS 2.0, an extension of ChronoEOS, is presented. This new version can record the events that occur in multiple industrial robotic arms by deploying a Smart Contract in the EOSIO blockchain so that all events are immutably recorded in the blockchain. Furthermore, the new version allows using a unique fingerprint of the robot before registering an event in the blockchain. This fingerprint depends only on the characteristics of the operation and configuration of the robot. For this reason, ChronoEOS 2.0 not only increase the ability of ChronoEOS in terms of handling multiple devices but also increases the security and reliability of the operations. Finally, in this study, we verify that the new improvements have little impact on the hosting resources (RAM and Network are not altered, while CPU consumption is slightly higher due to the device fingerprinting module). |
first_indexed | 2024-03-11T04:32:09Z |
format | Article |
id | doaj.art-888fdef21a3a4fd3b6bf2aa2a9857f0b |
institution | Directory Open Access Journal |
issn | 2624-6511 |
language | English |
last_indexed | 2024-03-11T04:32:09Z |
publishDate | 2023-03-01 |
publisher | MDPI AG |
record_format | Article |
series | Smart Cities |
spelling | doaj.art-888fdef21a3a4fd3b6bf2aa2a9857f0b2023-11-17T21:21:05ZengMDPI AGSmart Cities2624-65112023-03-016289791210.3390/smartcities6020043ChronoEOS 2.0: Device Fingerprinting and EOSIO Blockchain Technology for On-Running Forensic Analysis in an IoT EnvironmentJosé Álvaro Fernández-Carrasco0Xabier Echeberria-Barrio1Daniel Paredes-García2Francesco Zola3Raul Orduna-Urrutia4Fundación Vicomtech, Digital Security Department, Basque Research and Technology Alliance (BRTA), Mikeletegi 57, 20009 Donostia-San Sebastián, SpainFundación Vicomtech, Digital Security Department, Basque Research and Technology Alliance (BRTA), Mikeletegi 57, 20009 Donostia-San Sebastián, SpainFundación Vicomtech, Digital Security Department, Basque Research and Technology Alliance (BRTA), Mikeletegi 57, 20009 Donostia-San Sebastián, SpainFundación Vicomtech, Digital Security Department, Basque Research and Technology Alliance (BRTA), Mikeletegi 57, 20009 Donostia-San Sebastián, SpainFundación Vicomtech, Digital Security Department, Basque Research and Technology Alliance (BRTA), Mikeletegi 57, 20009 Donostia-San Sebastián, SpainIn industrial environments there are critical devices, so their correct operation must be ensured. In particular, having a secure record of the different events related to these devices is essential. Thus, this record can be used in future forensic investigations in case of accidents or production failures. In this sense, blockchain technology can bring reliability to the event log. In this paper, ChronoEOS 2.0, an extension of ChronoEOS, is presented. This new version can record the events that occur in multiple industrial robotic arms by deploying a Smart Contract in the EOSIO blockchain so that all events are immutably recorded in the blockchain. Furthermore, the new version allows using a unique fingerprint of the robot before registering an event in the blockchain. This fingerprint depends only on the characteristics of the operation and configuration of the robot. For this reason, ChronoEOS 2.0 not only increase the ability of ChronoEOS in terms of handling multiple devices but also increases the security and reliability of the operations. Finally, in this study, we verify that the new improvements have little impact on the hosting resources (RAM and Network are not altered, while CPU consumption is slightly higher due to the device fingerprinting module).https://www.mdpi.com/2624-6511/6/2/43EOSIO blockchainforensic analysisdevice fingerprintindustrial security |
spellingShingle | José Álvaro Fernández-Carrasco Xabier Echeberria-Barrio Daniel Paredes-García Francesco Zola Raul Orduna-Urrutia ChronoEOS 2.0: Device Fingerprinting and EOSIO Blockchain Technology for On-Running Forensic Analysis in an IoT Environment Smart Cities EOSIO blockchain forensic analysis device fingerprint industrial security |
title | ChronoEOS 2.0: Device Fingerprinting and EOSIO Blockchain Technology for On-Running Forensic Analysis in an IoT Environment |
title_full | ChronoEOS 2.0: Device Fingerprinting and EOSIO Blockchain Technology for On-Running Forensic Analysis in an IoT Environment |
title_fullStr | ChronoEOS 2.0: Device Fingerprinting and EOSIO Blockchain Technology for On-Running Forensic Analysis in an IoT Environment |
title_full_unstemmed | ChronoEOS 2.0: Device Fingerprinting and EOSIO Blockchain Technology for On-Running Forensic Analysis in an IoT Environment |
title_short | ChronoEOS 2.0: Device Fingerprinting and EOSIO Blockchain Technology for On-Running Forensic Analysis in an IoT Environment |
title_sort | chronoeos 2 0 device fingerprinting and eosio blockchain technology for on running forensic analysis in an iot environment |
topic | EOSIO blockchain forensic analysis device fingerprint industrial security |
url | https://www.mdpi.com/2624-6511/6/2/43 |
work_keys_str_mv | AT josealvarofernandezcarrasco chronoeos20devicefingerprintingandeosioblockchaintechnologyforonrunningforensicanalysisinaniotenvironment AT xabierecheberriabarrio chronoeos20devicefingerprintingandeosioblockchaintechnologyforonrunningforensicanalysisinaniotenvironment AT danielparedesgarcia chronoeos20devicefingerprintingandeosioblockchaintechnologyforonrunningforensicanalysisinaniotenvironment AT francescozola chronoeos20devicefingerprintingandeosioblockchaintechnologyforonrunningforensicanalysisinaniotenvironment AT raulordunaurrutia chronoeos20devicefingerprintingandeosioblockchaintechnologyforonrunningforensicanalysisinaniotenvironment |