Data Privacy in IoT Equipped Future Smart Homes

Khodabakhsh, Athar; Yayilgan, Sule Yildirim

doi:10.48550/arxiv.2008.04979

Cited by 1 publication

(1 citation statement)

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“…Smart services focus on providing recommendations to users and bring more intelligence to information and communications technology applications used in daily life. Smart homes get many advantages in terms of control management, cost, personal data protection, security, and privacy all of which benefits users as well as companies [12].…”

Section: Introductionmentioning

confidence: 99%

Anomaly Detection using Machine Learning to Discover Sensor Tampering in IoT Systems

Pathak

Saguna

Mitra

et al. 2021

ICC 2021 - IEEE International Conference on Communications

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With the rapid growth of the Internet of Things (IoT) applications in smart regions/cities, for example, smart healthcare, smart homes/offices, there is an increase in security threats and risks. The IoT devices solve real-world problems by providing real-time connections, data and information. Besides this, the attackers can tamper with sensors, add or remove them physically or remotely. In this study, we address the IoT security sensor tampering issue in an office environment. We collect data from real-life settings and apply machine learning to detect sensor tampering using two methods. First, a real-time view of the traffic patterns is considered to train our isolation forest-based unsupervised machine learning method for anomaly detection. Second, based on traffic patterns, labels are created, and the decision tree supervised method is used, within our novel Anomaly Detection using Machine Learning (AD-ML) system. The accuracy of the two proposed models is presented. We found 84% with silhouette metric accuracy of isolation forest. Moreover, the result based on 10 cross-validations for decision trees on the supervised machine learning model returned the highest classification accuracy of 91.62% with the lowest false positive rate.

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Section: Introductionmentioning

confidence: 99%