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Maximizing security by integrating OPSEC and AI for enhanced defense strategies

bracu.degree.levelUndergraduate
bracu.type.groupStudent Works
datacite.rightsOpen Access
dc.contributor.advisorHossain, Muhammad Iqbal
dc.contributor.authorFerdous, Raiyan
dc.contributor.authorYeahia, Mamsad Ibn
dc.contributor.authorRafeed, Munib Fahmid
dc.contributor.authorMajid, Nafiul
dc.contributor.departmentDepartment of Computer Science and Engineering
dc.date.accessioned2025-05-12T05:46:19Z
dc.date.available2025-05-12T05:46:19Z
dc.date.copyright2024
dc.date.issued2024-12
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 59-62).
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.en_US
dc.description.abstractOperational Security (OPSEC) is a risk and security management process and approach that first classifies information. There are five steps in OPSEC and the most important step is to identify and analyze potential threats and vulnerabilities. Analyzing threats and vulnerabilities can be done using manual penetration and VAPT where testers simulate real-world attacks the system may face in the future. Moreover, implementing improved machine learning algorithms can detect threats more robustly. By incorporating artificial intelligence with OPSEC, we can mitigate most of these drawbacks. This research identifies four threats; DDoS, Data Breach, Malware, and Phishing and detects them with particular ML/AI models and improves the performance of those models by optimizing. Moreover, this research implemented Explainable-AI (SHAP) in order to easily explain and interpret the models.en_US
dc.description.degreeBachelor of Science in Computer Science
dc.description.statementofresponsibilityRaiyan Ferdous
dc.description.statementofresponsibilityMamsad Ibn Yeahia
dc.description.statementofresponsibilityMunib Fahmid Rafeed
dc.description.statementofresponsibilityNafiul Majid
dc.format.extent68 pages
dc.identifier.otherID 21101127
dc.identifier.otherID 21101163
dc.identifier.otherID 24341128
dc.identifier.otherID 21101169
dc.identifier.urihttp://hdl.handle.net/10361/25877
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectOperational securityen_US
dc.subjectOPSECen_US
dc.subjectVAPTen_US
dc.subjectThreat modelingen_US
dc.subjectVulnerabilityen_US
dc.subjectData breachen_US
dc.subjectCyber threatsen_US
dc.subjectPenetration testingen_US
dc.subjectDDoSen_US
dc.subjectEx-AIen_US
dc.subject.lcshComputer networks--Security measures.
dc.subject.lcshComputational intelligence.
dc.subject.lcshData protection.
dc.titleMaximizing security by integrating OPSEC and AI for enhanced defense strategiesen_US
dc.typeThesisen_US

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