تقرير
Smart-home anomaly detection using combination of in-home situation and user behavior
| العنوان: | Smart-home anomaly detection using combination of in-home situation and user behavior |
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| المؤلفون: | Yamauchi, Masaaki, Tanaka, Masahiro, Ohsita, Yuichi, Murata, Masayuki, Ueda, Kensuke, Kato, Yoshiaki |
| سنة النشر: | 2021 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Cryptography and Security, Electrical Engineering and Systems Science - Systems and Control |
| الوصف: | Internet-of-things (IoT) devices are vulnerable to malicious operations by attackers, which can cause physical and economic harm to users; therefore, we previously proposed a sequence-based method that modeled user behavior as sequences of in-home events and a base home state to detect anomalous operations. However, that method modeled users' home states based on the time of day; hence, attackers could exploit the system to maximize attack opportunities. Therefore, we then proposed an estimation-based detection method that estimated the home state using not only the time of day but also the observable values of home IoT sensors and devices. However, it ignored short-term operational behaviors. Consequently, in the present work, we propose a behavior-modeling method that combines home state estimation and event sequences of IoT devices within the home to enable a detailed understanding of long- and short-term user behavior. We compared the proposed model to our previous methods using data collected from real homes. Compared with the estimation-based method, the proposed method achieved a 15.4% higher detection ratio with fewer than 10% misdetections. Compared with the sequence-based method, the proposed method achieved a 46.0% higher detection ratio with fewer than 10% misdetections. Comment: 13 pages, 22 figures |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2109.14348 |
| رقم الأكسشن: | edsarx.2109.14348 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |