Privacy-Preserving CCTV Analytics for Cyber-Physical Threat Intelligence

Autor:	Jean-Baptiste Rouquier, Jürgen Neises, Adrien Besse
Rok vydání:	2021
Předmět:	Coping (psychology) Service (systems architecture) business.industry Computer science Cyber-physical system Computer security computer.software_genre Threat intelligence Analytics Data center Architecture business computer Edge computing
Zdroj:	Cyber-Physical Security for Critical Infrastructures Protection ISBN: 9783030697808 CPS4CIP
DOI:	10.1007/978-3-030-69781-5_1
Popis:	This paper describes the FUJITSU CCTV Analytics service (FCAS), a privacy-preserving CCTV surveillance module using AI based video analytics for cyber-physical threat intelligence. The design and architecture of a privacy preserving and thus GDPR friendly way to improve security by automatically analysing video feeds and sending events that can be interpreted as a threat to further analytics is illustrated. The system has been applied to several scenarios like data centre and at ATMs. The developments can also be applied to general public safety requests and may be utilized coping with the COVID-19 impacts. Finally, the solution shall be adapted to edge computing. First steps illustrate the capabilities of small form factor systems.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::bdfa15d1a41aece84e9e6b4162ec2757 https://doi.org/10.1007/978-3-030-69781-5_1 Zobrazit plný text záznamu