Adaptive Blockchain Technology for a Cybersecurity Framework in IIoT

Lucio, Yeison LLante; Villalba, Katerine Márceles; Donado, Siler Amador

doi:10.1109/rita.2022.3166857

Cited by 14 publications

(13 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…• Organization (ORG): Organizations are a fundamental part of a Hyperledger network, they are practically the participants in the network and it is considered that there is decentralization in a network as long as it is made up of several organizations [15].…”

Section: B Phase 2: Deployment Of the Selected Blockchain Technology ...mentioning

confidence: 99%

“…The peers or nodes are the anchor points for the applications that want to interact with the Blockchain network. These peers contain the smart contracts and ledgers used to encapsulate shared processes and shared information on a network, respectively [15].…”

Section: Peers (P)mentioning

confidence: 99%

“…• Certification Authority (CA): Since there can be many participants in a Blockchain network, they must be fully identified to have confidence in the transactions that can be carried out [15].…”

Section: Peers (P)mentioning

confidence: 99%

“…• Ledger(L): In Hyperledger, the concept of a ledger is used in which factual information about the state of the entire Blockchain is stored [15].…”

Section: Peers (P)mentioning

confidence: 99%

“…The computers are configured nodes that are in charge of receiving batches of transactions that are ordered and packaged in blocks [15].…”

Section: Orders (O)mentioning

confidence: 99%

See 4 more Smart Citations

Validation of Cybersecurity Framework for Threat Mitigation

Llanten-Lucio

Donado²,

Villalba³

2022

Rev. Fac. Ing.

Self Cite

View full text Add to dashboard Cite

Currently on the Internet there are many threats that threaten the security of the information of users who daily access this network using different devices that connect from their homes or organizations that in many cases do not have security controls enough and end up exposing themselves to all those threats that grow over time. That is why this article aims to propose the validation of a cybersecurity framework that allows mitigating and reducing risks to increase security levels through the implementation of controls for homes and organizations using emerging technologies such as: IoT, Blockchain and Deep Learning. The foregoing was carried out with the methodological approach of action research starting from the improvement of the process in search of transformation, thus obtaining as results the integration of the aforementioned methodologies for the detection of possible malicious hosts within an internal network through an intelligent analysis of the traffic that passes through the same network in order to intelligently generate rules in intrusion detection systems (IDS) in an automated way and that these rules can in turn be distributed through a secure channel using the Blockchain technology, to finally guarantee the integrity of said rules and that also allows maintaining the immutability and synchronization of the same information with all the devices connected to the framework.

show abstract

Section: B Phase 2: Deployment Of the Selected Blockchain Technology ...mentioning

confidence: 99%

Section: Peers (P)mentioning

confidence: 99%

Section: Peers (P)mentioning

confidence: 99%

“…• Ledger(L): In Hyperledger, the concept of a ledger is used in which factual information about the state of the entire Blockchain is stored [15].…”

Section: Peers (P)mentioning

confidence: 99%

“…The computers are configured nodes that are in charge of receiving batches of transactions that are ordered and packaged in blocks [15].…”

Section: Orders (O)mentioning

confidence: 99%

See 3 more Smart Citations

Validation of Cybersecurity Framework for Threat Mitigation

Llanten-Lucio

Donado²,

Villalba³

2022

Rev. Fac. Ing.

Self Cite

View full text Add to dashboard Cite

show abstract

Automated cyberattack detection using optimal ensemble deep learning model

Vaiyapuri,

Shankar,

Rajendran

et al. 2023

Trans Emerging Tel Tech

View full text Add to dashboard Cite

In recent times, the Industrial Internet of Things (IIoT) has developed significantly. In the application of automation, and intelligence, industrial digitalization introduced cyber risks, and the varied and complex industrial IoT platform presented a novel attack surface for network invaders. Several Intrusion Detection Systems (IDS) were advanced recently as many computer networks exposure to privacy and security threats. Availability, Data confidentiality, and integrity, the damage will happen in case of IDS prevention failure. Traditional methods were ineffective in dealing with advanced attacks. Advanced deep learning (DL) methods were designed for automatic ID and abnormal behavior detection of networks. Therefore, this article focuses on the design of Improved Reptile Search Optimization with Ensemble Deep Learning based Cybersecurity (IRSO‐EDLCS) technique in the IIoT environment. The major aim of the IRSO‐EDLCS technique lies in the accurate identification of cyberattacks in the IIoT environment. To accomplish this, the presented IRSO‐EDLCS technique performs IRSO algorithm‐based feature selection (IRSO‐FS) technique. In addition, the IRSO‐EDLCS technique performs an ensemble of three DL models namely deep belief network (DBN), bidirectional gated recurrent unit (BiGRU), and autoencoder (AE). The hyperparameter tuning process is performed by a modified gray wolf optimizer (MGWO) to enhance detection process. To exhibit the improved performance of the IRSO‐EDLCS algorithm, a wide range of simulations were performed on the benchmark database. The experimental outcomes depict the betterment of the IRSO‐EDLCS technique over other existing models.

show abstract

Review and Comparison of US, EU, and UK Regulations on Cyber Risk/Security of the Current Blockchain Technologies: Viewpoint from 2023

Radanliev

2023

Rev Socionetwork Strat

View full text Add to dashboard Cite

The first cryptocurrency was invented in 2008/09, but the Blockchain-Web3 concept is still in its infancy, and the cyber risk is constantly changing. Cybersecurity should also be adapting to these changes to ensure security of personal data and continuation of operations. This article starts with a comparison of existing cybersecurity standards and regulations from the National Institute of Standards and Technology (NIST) and the International Organisation for Standardisation (ISO)—ISO27001, followed by a discussion on more specific and recent standards and regulations, such as the Markets in Crypto-Assets Regulation (MiCA), Committee on Payments and Market Infrastructures and the International Organisation of Securities Commissions (CPMI-IOSCO), and more general cryptography (and post-quantum cryptography), in the context of cybersecurity. These topics are followed up by a review of recent technical reports on cyber risk/security and a discussion on cloud security questions. Comparison of Blockchain cyber risk is also performed on the recent EU standards on cyber security, including European Cybersecurity Certification Scheme (EUCS)—cloud, and US standards—The National Vulnerability Database (NVD) Common Vulnerability Scoring System (CVSS). The study includes a review of Blockchain endpoint security, and new technologies e.g., IoT. The research methodology applied is a review and case study analysing secondary data on cybersecurity. The research significance is the integration of knowledge from the United States (US), the European Union (EU), the United Kingdom (UK), and international standards and frameworks on cybersecurity that can be alighted to new Blockchain projects. The results show that cybersecurity standards are not designed in close cooperation between the two major western blocks: US and EU. In addition, while the US is still leading in this area, the security standards for cryptocurrencies, internet-of-things, and blockchain technologies have not evolved as fast as the technologies have. The key finding from this study is that although the crypto-market has grown into a multi-trillion industry, the crypto-market has also lost over 70% since its peak, causing significant financial loss for individuals and cooperation’s. Despite this significant impact to individuals and society, cybersecurity standards and financial governance regulations are still in their infancy, specifically in the UK.

show abstract

Adaptive Blockchain Technology for a Cybersecurity Framework in IIoT

Cited by 14 publications

References 14 publications

Validation of Cybersecurity Framework for Threat Mitigation

Validation of Cybersecurity Framework for Threat Mitigation

Automated cyberattack detection using optimal ensemble deep learning model

Review and Comparison of US, EU, and UK Regulations on Cyber Risk/Security of the Current Blockchain Technologies: Viewpoint from 2023

Contact Info

Product

Resources

About