{"title":"CYBER-PHYSICAL SECURITY THROUGH FACIAL RECOGNITION AND SENSOR DATA ANALYSIS","authors":"Ivaylo Atanasov, D. Pilev","doi":"10.59957/jctm.v59.i2.2024.27","DOIUrl":null,"url":null,"abstract":"The 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.","PeriodicalId":38363,"journal":{"name":"Journal of Chemical Technology and Metallurgy","volume":"194 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Technology and Metallurgy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.59957/jctm.v59.i2.2024.27","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
The 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.
数字时代为创新和效率带来了巨大的机遇。然而,它也使企业、政府和个人面临一系列网络威胁,如数据泄露、网络攻击、勒索软件、恶意内鬼和身份盗用。这就需要实施强有力的网络安全措施来保护敏感信息,并确保所有关键 IT 系统的不间断运行。本文旨在提供一种用于网络物理安全的面部识别安全系统,该系统结合了神经网络和智能算法来评估安全漏洞的严重程度。该系统还包括根据面部识别以及二氧化碳和温度传感器的数据发出的严重程度从 1(低严重性)到 4(严重性)不等的警报。一旦发生安全漏洞,系统将提出事故响应计划。拟议的系统适用于办公室、工作区、服务器机房、数据中心和其他存储信息的区域,以加强实体安全和防范网络安全威胁。