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dc.contributor.author Eman Mukhtar, 01-134212-038
dc.contributor.author Maha Noor Zafar, 01-134212-078
dc.date.accessioned 2026-02-19T06:51:47Z
dc.date.available 2026-02-19T06:51:47Z
dc.date.issued 2025
dc.identifier.uri http://hdl.handle.net/123456789/20628
dc.description Supervised by Dr. Sabina Akhtar en_US
dc.description.abstract A greater number of phishing attacks on unsuspecting users has heightened the urgency of d eveloping stronger protective measures. The Phish Sentinel project aims at providing acomplete solution for detecting and preventing phishing attacks using machine learningmodels. Machine learning models will be used for analyzing URLs and website contentswhich will proactively provide users protection against phishing threats. This documentcomprises the Software Requirements Specification (SRS) and Software Design Specifica-tion (SDS) to present a comprehensive description of the project goals, methods, design,implementation, testing, and evaluation within a singular cohesive framework.iLeveraging sophisticated machine learning models, Phish Sentinel aspires to offer compre-hensive protection against phishing attacks. The design of Phish Sentinel encompasses anAI-model web page, a user dashboard to handle reports, and a machine learning pipelinefor classifying suspicious URLs using features like SSL certificates, blacklist status, anddomain age. This project provides adaptive security as well as an efficient, anticipatorystrategy against phishing attempts that continually change in sophistication. en_US
dc.language.iso en en_US
dc.publisher Computer Sciences en_US
dc.relation.ispartofseries BS(CS);P-3074
dc.subject Phish en_US
dc.subject Sentinel en_US
dc.title Phish Sentinel en_US
dc.type Project Reports en_US


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