RF Cloud for Cyberspace Intelligence

Wireless information networks have become a necessity of our day-to-day life. Over a billion Wi-Fi access points, hundreds of thousands of cell towers, and billions of IoT devices, using a variety of wireless technologies, create the infrastructure that enables this technology to access everyone, ev...

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Autores principales:	Kaveh Pahlavan, Julang Ying, Ziheng Li, Erin Solovey, John Patrick Loftus, Zehua Dong
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2020
Materias:	Motion detection gesture detection authentication security cyberspace smart world Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/ecd236f99f954bb3b7a6b7080b196a4d
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id	oai:doaj.org-article:ecd236f99f954bb3b7a6b7080b196a4d
record_format	dspace
spelling	oai:doaj.org-article:ecd236f99f954bb3b7a6b7080b196a4d2021-11-19T00:03:30ZRF Cloud for Cyberspace Intelligence2169-353610.1109/ACCESS.2020.2993548https://doaj.org/article/ecd236f99f954bb3b7a6b7080b196a4d2020-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9090822/https://doaj.org/toc/2169-3536Wireless information networks have become a necessity of our day-to-day life. Over a billion Wi-Fi access points, hundreds of thousands of cell towers, and billions of IoT devices, using a variety of wireless technologies, create the infrastructure that enables this technology to access everyone, everywhere. The radio signal carrying the wireless information, propagates from antennas through the air and creates a radio frequency (RF) cloud carrying a huge amount of data that is commonly accessible by anyone. The big data of the RF cloud includes information about the transmitter type and addresses, embedded in the information packets; as well as features of the RF signal carrying the message, such as received signal strength (RSS), time of arrival (TOA), direction of arrival (DOA), channel impulse response (CIR), and channel state information (CSI). We can benefit from the big data contents of the messages as well as the temporal and spatial variations of their RF propagation characteristics to engineer intelligent cyberspace applications. This paper provides a holistic vision of emerging cyberspace applications and explains how they benefit from the RF cloud to operate. We begin by introducing the big data contents of the RF cloud. Then, we explain how innovative cyberspace applications are emerging that benefit from this big data. We classify these applications into three categories: wireless positioning systems, gesture and motion detection technologies, and authentication and security techniques. We explain how Wi-Fi, cell-tower, and IoT wireless positioning systems benefit from big data of the RF cloud. We discuss how researchers are studying applications of RF cloud features for motion, activity and gesture detection for human-computer interaction, and we show how authentication and security applications benefit from RF cloud characteristics.Kaveh PahlavanJulang YingZiheng LiErin SoloveyJohn Patrick LoftusZehua DongIEEEarticleMotion detectiongesture detectionauthenticationsecuritycyberspacesmart worldElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 8, Pp 89976-89987 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Motion detection gesture detection authentication security cyberspace smart world Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Motion detection gesture detection authentication security cyberspace smart world Electrical engineering. Electronics. Nuclear engineering TK1-9971 Kaveh Pahlavan Julang Ying Ziheng Li Erin Solovey John Patrick Loftus Zehua Dong RF Cloud for Cyberspace Intelligence
description	Wireless information networks have become a necessity of our day-to-day life. Over a billion Wi-Fi access points, hundreds of thousands of cell towers, and billions of IoT devices, using a variety of wireless technologies, create the infrastructure that enables this technology to access everyone, everywhere. The radio signal carrying the wireless information, propagates from antennas through the air and creates a radio frequency (RF) cloud carrying a huge amount of data that is commonly accessible by anyone. The big data of the RF cloud includes information about the transmitter type and addresses, embedded in the information packets; as well as features of the RF signal carrying the message, such as received signal strength (RSS), time of arrival (TOA), direction of arrival (DOA), channel impulse response (CIR), and channel state information (CSI). We can benefit from the big data contents of the messages as well as the temporal and spatial variations of their RF propagation characteristics to engineer intelligent cyberspace applications. This paper provides a holistic vision of emerging cyberspace applications and explains how they benefit from the RF cloud to operate. We begin by introducing the big data contents of the RF cloud. Then, we explain how innovative cyberspace applications are emerging that benefit from this big data. We classify these applications into three categories: wireless positioning systems, gesture and motion detection technologies, and authentication and security techniques. We explain how Wi-Fi, cell-tower, and IoT wireless positioning systems benefit from big data of the RF cloud. We discuss how researchers are studying applications of RF cloud features for motion, activity and gesture detection for human-computer interaction, and we show how authentication and security applications benefit from RF cloud characteristics.
format	article
author	Kaveh Pahlavan Julang Ying Ziheng Li Erin Solovey John Patrick Loftus Zehua Dong
author_facet	Kaveh Pahlavan Julang Ying Ziheng Li Erin Solovey John Patrick Loftus Zehua Dong
author_sort	Kaveh Pahlavan
title	RF Cloud for Cyberspace Intelligence
title_short	RF Cloud for Cyberspace Intelligence
title_full	RF Cloud for Cyberspace Intelligence
title_fullStr	RF Cloud for Cyberspace Intelligence
title_full_unstemmed	RF Cloud for Cyberspace Intelligence
title_sort	rf cloud for cyberspace intelligence
publisher	IEEE
publishDate	2020
url	https://doaj.org/article/ecd236f99f954bb3b7a6b7080b196a4d
work_keys_str_mv	AT kavehpahlavan rfcloudforcyberspaceintelligence AT julangying rfcloudforcyberspaceintelligence AT zihengli rfcloudforcyberspaceintelligence AT erinsolovey rfcloudforcyberspaceintelligence AT johnpatrickloftus rfcloudforcyberspaceintelligence AT zehuadong rfcloudforcyberspaceintelligence
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RF Cloud for Cyberspace Intelligence

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