CYBER-PHYSICAL SECURITY THROUGH FACIAL RECOGNITION AND SENSOR DATA ANALYSIS

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creativework.keywordsartificial intelligence, convolutional neural network, cybersecurity, facial recognition
creativework.publisherUniversity of Chemical Technology and Metallurgyen
dc.contributor.authorAtanasov I.
dc.contributor.authorPilev D.
dc.date.accessioned2024-07-10T14:27:06Z
dc.date.accessioned2024-07-10T14:51:09Z
dc.date.available2024-07-10T14:27:06Z
dc.date.available2024-07-10T14:51:09Z
dc.date.issued2024-01-01
dc.description.abstractThe digital age has brought tremendous opportunities for innovation and efficiency. However, it has also exposed businesses, governments, and individuals to a range of cyber threats, such as data breaches, network attacks, ransomware, malicious insiders, and identity theft. This requires the implementation of robust cybersecurity measures to safeguard sensitive information and ensure the uninterrupted operation of all critical IT systems. This paper aims to provide a facial recognition security system for cyber-physical security that incorporates a neural network and intelligent algorithms to assess the severity level of security breaches. The system also includes alarms with severity levels ranging from 1 (low severity) to 4 (critical), based on facial recognition and data from carbon dioxide and temperature sensors. In the event of a security breach, an incident response plan is presented. The proposed system is applicable to offices, workspaces, server rooms, data centers and other areas where information is stored, to enhance physical security and protect against cybersecurity threats.
dc.identifier.doi10.59957/jctm.v59.i2.2024.27
dc.identifier.issn1314-7978
dc.identifier.issn1314-7471
dc.identifier.scopusSCOPUS_ID:85186883586en
dc.identifier.urihttps://rlib.uctm.edu/handle/123456789/923
dc.language.isoen
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85186883586&origin=inward
dc.titleCYBER-PHYSICAL SECURITY THROUGH FACIAL RECOGNITION AND SENSOR DATA ANALYSIS
dc.typeArticle
oaire.citation.issue2
oaire.citation.volume59
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