Real-Time Monitoring and Anomaly Detection in Cloud-Based IoT Networks

Title

Real-Time Monitoring and Anomaly Detection in Cloud-Based IoT Networks

Creator

Sharma, Pradeep; Logeshwaran, J.

Description

IoT devices have seen explosive growth, causing a data explosion, which makes it almost impossible to manage and monitor these networks. This has led to a demand for solutions providing real-time monitoring and detection of anomalies in cloud-based Internet of Things (IoT) networks. In cybersecurity, the term real-time monitoring denotes the ongoing analysis of data and network performance to detect potential problems. It allows for the identification of anomalies and possible weaknesses in the system. In contrast, anomaly detection is the process of finding deviations from what is considered normal for a system or data. Within cloud-based IoT networks, this might involve identifying abnormal traffic patterns or unusual activity from devices. To solve these challenges, we propose a cloud computing and machine learning-based solution. IoT devices generate a massive amount of data, which is processed in real-time and stored on the cloudbased infrastructure. Many machine learning algorithms analyze these data algorithms to identify anomalies or threats to security. This solution provides an active early warning detection of security breaches from the network management perspective, along with timely response in the case of abnormal behaviour. It will ultimately result in improved cloud-based networks for IoT devices with regard to reliability, security, and performance. This solution can be a key factor in driving the mass implementation of IoT in various sectors. 2025 IEEE.

Source

2025 International Conference on Networks and Cryptology, NETCRYPT 2025;pp.448-452

Date

01-01-2025

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

considered; cybersecurity; explosive; identification; implementation; impossible; management; monitoring

Coverage

Sharma P., Service Now, United States; Logeshwaran J., Christ University, Department of Computer Science, Karnataka, Bengaluru, 560029, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISBN: 979-833152605-4;

Format

online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/NETCRYPT65877.2025.11102267

https://www.scopus.com/pages/publications/105015531970?origin=resultslist