Enhancing Security and Scalability in Cloud Computing for IoT Integration

The fusion of Cloud Computing and Internet of Things (IoT) has ushered in revolutionary capabilities across different sectors, such as smart cities, healthcare, industrial automation, and agriculture. Yet the two technologies' integration also entails immense challenges, especially with regard to security and scalability. Since IoT devices produce tremendous volumes of data, the need for cloud infrastructure to process, manage, and store such data in real-time increases every day. This paper introduces an in-depth study on the improvement of security and scalability within cloud computing environments to enable seamless integration of IoT systems. The paper proceeds with an examination of the native weaknesses in cloud-based IoT structures, including unauthorized access, data leaks, identity impersonation, and Denial of Service (DoS) attacks. The paper also explores the shortcomings of available cloud infrastructures to support the continuously growing burden from millions of IoT devices in connection. The paper assesses recent industry trends and research methods, highlighting loopholes and dynamics in different security protocols and scalability measures. To meet these demands, the paper suggests a multi-layered security model that utilizes sophisticated encryption methods, secure authentication protocols, and anomaly detection software to protect information and preserve user privacy. Furthermore, it investigates the application of scalable cloud models like hybrid cloud and edge computing in mitigating latency and enhancing responsiveness for time-critical IoT applications.

Authors

Publication Details

Journal
Journal of Emerging Technologies and Innovative Research
Published
2025-01-01
DOI
https://doi.org/10.56975/jetir.v12i4.559073
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing Security and Scalability in Cloud Computing for IoT Integration

ABDULAZIZ ABDULLAH MOHAMMED GHALIB
Journal of Emerging Technologies and Innovative Research
IoT and Edge/Fog Computing
article

Enhancing Security and Scalability in Cloud Computing for IoT Integration

ABDULAZIZ ABDULLAH MOHAMMED GHALIB
article en

Abstract

The fusion of Cloud Computing and Internet of Things (IoT) has ushered in revolutionary capabilities across different sectors, such as smart cities, healthcare, industrial automation, and agriculture. Yet the two technologies' integration also entails immense challenges, especially with regard to security and scalability. Since IoT devices produce tremendous volumes of data, the need for cloud infrastructure to process, manage, and store such data in real-time increases every day. This paper introduces an in-depth study on the improvement of security and scalability within cloud computing environments to enable seamless integration of IoT systems. The paper proceeds with an examination of the native weaknesses in cloud-based IoT structures, including unauthorized access, data leaks, identity impersonation, and Denial of Service (DoS) attacks. The paper also explores the shortcomings of available cloud infrastructures to support the continuously growing burden from millions of IoT devices in connection. The paper assesses recent industry trends and research methods, highlighting loopholes and dynamics in different security protocols and scalability measures. To meet these demands, the paper suggests a multi-layered security model that utilizes sophisticated encryption methods, secure authentication protocols, and anomaly detection software to protect information and preserve user privacy. Furthermore, it investigates the application of scalable cloud models like hybrid cloud and edge computing in mitigating latency and enhancing responsiveness for time-critical IoT applications.

Journal of Emerging Technologies and Innovative ResearchVol. 12(4)
Openalex Percentile: Top 84%
IoT and Edge/Fog Computing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.