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Introduction:

Anomaly detection in sensor data plays a crucial role in ensuring the security and reliability of IoT networks. With the increasing number of devices connected to the internet, the need for efficient anomaly detection algorithms has become more important than ever. By detecting abnormal behavior in sensor data, anomalies can be identified and addressed promptly, preventing potential security breaches or system failures. This thesis aims to explore different anomaly detection techniques for sensor data in IoT networks, evaluate their performance, and provide recommendations for improving anomaly detection in IoT environments.

Table of Contents:

Chapter 1: Introduction
1.1 Background
1.2 Problem Statement
1.3 Objectives of Study
1.4 Limitations of Study
1.5 Scope of Study

Chapter 2: Literature Review
2.1 Overview of IoT Networks
2.2 Anomaly Detection Techniques
2.3 Applications of Anomaly Detection in IoT Networks
2.4 Challenges in Anomaly Detection for Sensor Data

Chapter 3: Research Methodology
3.1 Data Collection
3.2 Data Preprocessing
3.3 Anomaly Detection Algorithm Selection
3.4 Performance Evaluation Metrics

Chapter 4: Discussion of Findings
4.1 Comparison of Anomaly Detection Techniques
4.2 Analysis of Performance Metrics
4.3 Recommendations for Improving Anomaly Detection in IoT Networks

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Conclusions
5.3 Future Research Directions

Thesis Overview:

Anomaly detection in sensor data is a critical aspect of ensuring the security and reliability of IoT networks. This thesis will explore various anomaly detection techniques for sensor data in IoT environments, evaluate their performance, and provide insights into improving anomaly detection in IoT networks. The literature review will provide a comprehensive overview of IoT networks, anomaly detection techniques, their applications, and challenges. The research methodology will outline the data collection process, preprocessing steps, algorithm selection, and performance evaluation metrics. The discussion of findings will compare different anomaly detection techniques, analyze performance metrics, and provide recommendations for enhancing anomaly detection in IoT networks. The conclusion and summary chapter will summarize the findings, draw conclusions, and suggest future research directions in the field of anomaly detection for sensor data in IoT networks.

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