Comprehensive Survey on Detection of Anomalies in Edge Computing Network and Deep Learning Solutions

Sonali Jadhav, Arun Kulkarni

2024

Abstract

Edge computing is an innovative computing model that plays an essential role in offering faster computation, increased security, and lower transfer costs to the production applications that run on collection of IoT devices, sensors, and the network. Today, IoT has become extensively utilized technology in a variety of applications, including medical, industrial, agriculture, transport, manufacturing, surveillance and so on. Edge computing involves processing a variety of data closer to its source, allowing for faster processing rates over the large volumes and more effective outcomes in real time. However, with the increasing number and complexity of IoT devices in Edge networks, as well as the never-ending accumulation of network data, monitoring in Edge networks and identifying abnormal network behavior is getting increasingly challenging. Anomaly detection is a significant issue that has received extensive attention across all range of disciplines and application do-mains. Deep Learning is a branch of machine learning that deals with approaches inspired by the structure and function of artificial neural networks which can be used to solve many real-world problems. The objective of this research paper is to survey and illuminate the role of deep learning techniques in tackling the edge computing anomalies and provides an extensive overview on deep Learning techniques used for detecting them. The research work also covers the case study on anomaly detection over edge computing using deep neural network (DNN) and generative adversarial network (GAN) models.

Paper Citation

in Harvard Style

Jadhav S. and Kulkarni A. (2024). Comprehensive Survey on Detection of Anomalies in Edge Computing Network and Deep Learning Solutions. In Proceedings of the 1st International Conference on Cognitive & Cloud Computing - Volume 1: IC3Com; ISBN 978-989-758-739-9, SciTePress, pages 37-45. DOI: 10.5220/0013344100004646

in Bibtex Style

@conference{ic3com24,
author={Sonali Jadhav and Arun Kulkarni},
title={Comprehensive Survey on Detection of Anomalies in Edge Computing Network and Deep Learning Solutions},
booktitle={Proceedings of the 1st International Conference on Cognitive & Cloud Computing - Volume 1: IC3Com},
year={2024},
pages={37-45},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013344100004646},
isbn={978-989-758-739-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Cognitive & Cloud Computing - Volume 1: IC3Com
TI - Comprehensive Survey on Detection of Anomalies in Edge Computing Network and Deep Learning Solutions
SN - 978-989-758-739-9
AU - Jadhav S.
AU - Kulkarni A.
PY - 2024
SP - 37
EP - 45
DO - 10.5220/0013344100004646
PB - SciTePress