Strategic Approaches to Intrusion Detection in Cloud-IoT Ecosystem

5Learning Safeguards: Leveraging Machine Learning for Anomaly Detection in Cloud – IoT Networks

Swastika Kayal¹ and Soumen Santra^2*

¹Department of Computer Science and Engineering, St. Thomas’ College of Engineering and Technology, Kolkata, West Bengal, India

²Department of Master of Computer Applications, Techno International New Town, Kolkata, West Bengal, India

Abstract

Cloud computing has a huge impact on Intrusion Detection or Anomaly Detection having some influence of Machine Learning in it. Leveraging machine learning, we improvise cost estimation by maintaining performance and efficiency within an organization, particularly in managing IT infrastructure. This paper explores the applied algorithms of machine learning techniques for detection of anomaly in cloud-based environment with a collaboration of IoT techniques. Detection is made mainly based on use of machine learning techniques to analyze current data for making predictions about future events, trends or behaviors. This paper has an extensive explanation using concept like pattern recognition to identify anomalies or trends, scalability showing capability to handle growing workforce along with its potential to accommodate growth and Big Data Analysis. In the context of Anomaly detection, recent trends have a high value with healthcare landscape where we can see the value or predictive analysis in the field of medical sciences. By addressing these challenges and by finding solutions to it, IoMT healthcare networks ...