 |
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
|
Issue: July 2026
Volume 11 | Issue 7
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 122
Article Submitted : 25330
Article Published : 9497
Total Authors : 25208
Total Reviewer : 873
Total Countries : 172
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | Enhancing Secure Cryptography for Sustainable IoT Applications through Artificial Intelligence and Machine Learning |
| Authors Name: | Kritika Purohit , Dr. A.K. Sharma |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_213588
|
| Published Paper Id: | IJRTI2606102 |
| Published In: | Volume 11 Issue 6, June-2026 |
| DOI: | |
| Abstract: | The Internet of Things (IoT) has revolutionized modern digital infrastructure by connecting billions of devices across domains such as healthcare, smart cities, industrial automation, and transportation. However, the rapid growth of IoT networks has also introduced significant security challenges due to the limited computational power, memory, and energy resources of many connected devices. Traditional cryptographic techniques provide essential security services, but their implementation in resource-constrained environments often results in increased computational overhead and reduced efficiency. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as promising technologies for enhancing IoT security by enabling intelligent threat detection, adaptive authentication, dynamic key management, and real-time security monitoring. In addition to strengthening cybersecurity, these technologies can optimize resource utilization and support sustainable IoT operations by reducing unnecessary computational and energy consumption. This paper reviews the role of AI and ML in improving cryptographic security for sustainable IoT applications. It discusses key security challenges, examines recent advancements in AI-assisted cryptographic mechanisms, and proposes the Adaptive Intelligent Cryptographic Engine (AICE), a conceptual framework that integrates lightweight cryptography with intelligent security techniques. The study highlights the potential of AI-driven cryptographic solutions to develop secure, scalable, and energy-efficient IoT ecosystems capable of addressing future cybersecurity demands. |
| Keywords: | Internet of Things (IoT), Artificial Intelligence, Machine Learning, Cryptography, IoT Security, Lightweight Cryptography, Sustainable IoT, Cybersecurity. |
| Cite Article: | "Enhancing Secure Cryptography for Sustainable IoT Applications through Artificial Intelligence and Machine Learning", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 6, page no.a950-a969, June-2026, Available :http://www.ijrti.org/papers/IJRTI2606102.pdf |
| Downloads: | 00097 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2606102
Registration ID:213588
Published In: Volume 11 Issue 6, June-2026
DOI (Digital Object Identifier):
Page No: a950-a969 Country: Jodhpur, Rajasthan, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2606102 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2606102 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2026 - All Rights Reserved - IJRTI | |||