Enhancing Identification of IoT Anomalies in Smart Homes Using Secure Blockchain Technology

Author:

Tahir Sidra1

Affiliation:

1. UIIT, Pakistan

Abstract

Numerous technologies that automate processes and simplify our lives are included in smart homes. These gadgets may be helpful for various things, including temperature, lighting, and security access. Smart homes fundamentally enable remote control of equipment and appliances for homeowners via the internet of things (IoT) platform. Smart houses are able to understand their owners' routines and modify in accordance with their capacity for self-learning. The requirement to identify abnormalities in data created by smart homes arises from the necessity of convenience and cost savings in such a setting, as well as from the involvement of numerous devices. The topic of anomaly detection using deep learning is covered in this chapter. Additionally, the suggested solution is more secure because to the usage of block chain technology. Results show that the suggested strategy has exceptional accuracy and recall.

Publisher

IGI Global

Reference46 articles.

1. Blockchain for Internet of Things (IoT) Research Issues Challenges \& Future Directions: A Review.;M.Alamri;Int. J. Comput. Sci. Netw. Secur,2019

2. Alferidah, D. K., & Jhanjhi, N. Z. (2020). A Review on Security and Privacy Issues and Challenges. Internet of Things,20(4), 263–285.

3. Classification of Indoor Environments for IoT Applications: A Machine Learning Approach

4. A review on smart home present state and challenges: linked to context-awareness internet of things (IoT)

5. AD-IoT: Anomaly Detection of IoT Cyberattacks in Smart City Using Machine Learning

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