How Can the Adversary Effectively Identify Cellular IoT Devices Using LSTM Networks?

dc.contributor.authorLuo, Zhengping Jayen
dc.contributor.authorPitera, Willen
dc.contributor.authorZhao, Shangqingen
dc.contributor.authorLu, Zhuoen
dc.contributor.authorSagduyu, Yalinen
dc.date.accessioned2023-07-11T13:47:08Zen
dc.date.available2023-07-11T13:47:08Zen
dc.date.issued2023-06-01en
dc.date.updated2023-07-01T08:02:52Zen
dc.description.abstractThe Internet of Things (IoT) has become a key enabler for connecting edge devices with each other and the internet. Massive IoT services provided by cellular networks offer various applications such as smart metering and smart cities. Security of the massive IoT devices working alongside traditional devices such as smartphones and laptops has become a major concern. Protecting these IoT devices from being identified by malicious attackers is often the first line of defense for cellular IoT devices. In this paper, we provide an effective attacking method for identifying cellular IoT devices from cellular networks. Inspired by the characteristics of Long Short-Term Memory (LSTM) networks, we have developed a method that can not only capture context information but also adapt to the dynamic changes of the environment over time. Experimental validation shows a high detection rate with less than 10 epochs of training on public datasets.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1145/3586209.3591394en
dc.identifier.urihttp://hdl.handle.net/10919/115728en
dc.language.isoenen
dc.publisherACMen
dc.rightsIn Copyrighten
dc.rights.holderThe author(s)en
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.titleHow Can the Adversary Effectively Identify Cellular IoT Devices Using LSTM Networks?en
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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