2024
DOI: 10.3390/fi16040139
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A Comprehensive Review of Machine Learning Approaches for Anomaly Detection in Smart Homes: Experimental Analysis and Future Directions

Md Motiur Rahman,
Deepti Gupta,
Smriti Bhatt
et al.

Abstract: Detecting anomalies in human activities is increasingly crucial today, particularly in nuclear family settings, where there may not be constant monitoring of individuals’ health, especially the elderly, during critical periods. Early anomaly detection can prevent from attack scenarios and life-threatening situations. This task becomes notably more complex when multiple ambient sensors are deployed in homes with multiple residents, as opposed to single-resident environments. Additionally, the availability of da… Show more

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Cited by 2 publications
(1 citation statement)
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“…Adversaries can breach numerous susceptible IoT devices, take control of them, and create botnets and linked networks of infiltrated devices. These infected devices can then flood networks with traffic, causing significant delays and ML-based anomaly detection [4] offers a wide range of uses across sectors. The financial industry uses it for fraud detection, reporting and examining any unusual transactions or activity.…”
Section: Introductionmentioning
confidence: 99%
“…Adversaries can breach numerous susceptible IoT devices, take control of them, and create botnets and linked networks of infiltrated devices. These infected devices can then flood networks with traffic, causing significant delays and ML-based anomaly detection [4] offers a wide range of uses across sectors. The financial industry uses it for fraud detection, reporting and examining any unusual transactions or activity.…”
Section: Introductionmentioning
confidence: 99%