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Public cloud-base big alarm data analytics platform for large-scale physical security

Published: 30 May 2024 Publication History

Abstract

Along with the development of ICT technology, physical and building security services are also evolved. State-of-the-art sensors detect the slightest changes in movement, heat, smoke, light, vibration, etc. Most of the on-premise servers were used to provide building care services in the existing village or small city-scale areas. In this environment, we were able to provide reliable services to customers without any problems. However, there is a problem in providing services for large cities or the entire country. There is a limit to storing and analyzing a big amount of alarm data in the on-premise server. Furthermore, the detection mechanism determines actual intrusion based on pre-defined rule without data analytics. This mechanism has high false alarm ratio and error rate. To solve this problem, this paper introduces a public cloud-based platform that provides security services by collecting, storing, and analyzing alarm data simultaneously generated across the entire country. The proposed platform improves the accuracy of false intrusion determination through machine learning in public cloud. Compared to previous rule-base algorithm, our model improves false alarm detection ratio around 20%. It uses both structured and unstructured data sets to determine false alarms. This platform supports the security guard (commander) by visualizing the analysis results using Microsoft Power BI service. In addition, we provide statistical analysis results between alarm data and related weather conditions.

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    DSDE '24: Proceedings of the 2024 7th International Conference on Data Storage and Data Engineering
    February 2024
    103 pages
    ISBN:9798400716935
    DOI:10.1145/3653924
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 30 May 2024

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    Author Tags

    1. Big data
    2. Cloud computing
    3. alarm service
    4. physical security
    5. security alarm
    6. security service
    7. smart sensors

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