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Artificial intelligence for security measures against malicious links

bracu.degree.levelUndergraduate
bracu.type.groupStudent Works
datacite.rightsOpen Access
dc.contributor.advisorRasel, Annajiat Alim
dc.contributor.authorRinvee, Tajbiha Mehonaj
dc.contributor.authorSayara, Nowshin
dc.contributor.authorBhuiyan, Ziana Jesin
dc.contributor.departmentDepartment of Computer Science and Engineering
dc.date.accessioned2025-09-16T04:55:59Z
dc.date.available2025-09-16T04:55:59Z
dc.date.copyright2025
dc.date.issued2025-04
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 33-34).
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2025.en_US
dc.description.abstractThis paper analyzes the integration of artificial intelligence (AI) into security to impede the continual risk of malicious links. In a dynamic digital ecosystem, links create an ongoing challenge to user security. In this paper, we propose developing and implementing machine learning (ML) models that enable real-time detection and suppression of malicious links. Through training on diverse datasets of malicious links, the AI system can evolve strategies. Rigorous testing ensures the efficiency of the integrated protection. The outcome is to redefine security by amplifying an AI-driven solution, offering a proactive firewall against spam links, and improving overall digital safety for consumers.en_US
dc.description.degreeBachelor of Science in Computer Science
dc.description.statementofresponsibilityTajbiha Mehonaj Rinvee
dc.description.statementofresponsibilityNowshin Sayara
dc.description.statementofresponsibilityZiana Jesin Bhuiyan
dc.format.extent35 pages
dc.identifier.otherID 21301311
dc.identifier.otherID 21301149
dc.identifier.otherID 21301324
dc.identifier.urihttp://hdl.handle.net/10361/26752
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.subjectMachine learningen_US
dc.subjectArtificial intelligenceen_US
dc.subjectDigital ecosystemen_US
dc.subjectCybersecurityen_US
dc.subjectDigital safetyen_US
dc.subjectIntegrated protectionen_US
dc.subjectWeb securityen_US
dc.subjectURL filtering
dc.subjectNetwork securityen_US
dc.subject.lcshComputer networks--Security measures.
dc.subject.lcshComputer security.
dc.subject.lcshComputational intelligence.
dc.subject.lcshAnomaly detection (Computer security).
dc.titleArtificial intelligence for security measures against malicious linksen_US
dc.typeThesisen_US

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