A Novel Multi-Tiered Security Architecture for IoT: Integrating AI, Blockchain, and Efficient Cryptography

Clicks: 1
ID: 312889
2024
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #512 of 705 articles by views in Journal of Computing & Biomedical Informatics

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 705 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
The rapid expansion of the Internet of Things (IoT) has transformed numerous sectors by enabling smart connectivity and data-centric decision processes. Nevertheless, the swift growth of IoT networks poses significant security and privacy challenges due to their scale, heterogeneity, and the substantial amount of confidential information they transmit. This research proposes a layered approach to enhance the protection of IoT devices and their communications. The study explores several key technologies, including artificial intelligence-powered intrusion detection systems (IDS), authentication frameworks based on blockchain, and efficient cryptographic algorithms. The proposed model integrates machine learning techniques such as k-Nearest Neighbors (KNN) and Multi-Layer Perceptron (MLP) to identify and categorize anomalies in IoT data. Results indicate that both MLP and KNN performed exceptionally well, achieving accuracy rates of approximately 98% with minimal.
Reference Key
imported_1777057624_69ebbf58e2411 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Fatima Noor
Journal Journal of Computing & Biomedical Informatics
Year 2024
DOI
DOI not found
URL
https://jcbi.org/index.php/Main/article/view/739
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.