dc.contributor.advisor | Hossain, Dr.Muhammad Iqbal | |
dc.contributor.author | Bin Moshiur, Tasnimul | |
dc.contributor.author | Ullah, Mohammad Zafar | |
dc.contributor.author | Nawar, Nahian | |
dc.contributor.author | Tazwar, Tawsif Muhammed | |
dc.contributor.author | Nanjiba, Rifah | |
dc.date.accessioned | 2023-12-05T09:40:01Z | |
dc.date.available | 2023-12-05T09:40:01Z | |
dc.date.copyright | 2023 | |
dc.date.issued | 2023-01 | |
dc.identifier.other | ID: 18301014 | |
dc.identifier.other | ID: 18201153 | |
dc.identifier.other | ID: 19241015 | |
dc.identifier.other | ID: 18301012 | |
dc.identifier.other | ID: 19101522 | |
dc.identifier.uri | http://hdl.handle.net/10361/21925 | |
dc.description | This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023. | en_US |
dc.description | Cataloged from PDF version of thesis. | |
dc.description | Includes bibliographical references (pages 39-41). | |
dc.description.abstract | With the advancement in technology, fraudulent videos are becoming harder to de tect and easier to produce. Surveillance footage can serve as circumstantial evidence
when dealing with crimes, however when this footage is tampered with, there is a
great loss in evidence and the footage loses its value. To combat this growing prob lem, in this paper, we aim to find a new system to determine authenticity in a video
for security measures based on Blockchain & Deep Learning Tools. The importance
of Blockchain in this era of time is gradually increasing due its decentralized features,
fault-tolerance attribute, immutability. This paper is looking forward to introducing
a system which protects the surveillance footage gathered from a camera in a faster
and optimal approach so that the authenticity can be checked and protected. Our
goal is to implement a system which would secure the importance of crucial footage
as evidence. | en_US |
dc.description.statementofresponsibility | Tasnimul Bin Moshiur | |
dc.description.statementofresponsibility | Mohammad Zafar Ullah | |
dc.description.statementofresponsibility | Nahian Nawar | |
dc.description.statementofresponsibility | Tawsif Muhammed Tazwar | |
dc.description.statementofresponsibility | Rifah Nanjiba | |
dc.format.extent | 42 pages | |
dc.language.iso | en | en_US |
dc.publisher | Brac University | en_US |
dc.rights | Brac 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.subject | Blockchain | en_US |
dc.subject | Surveillance footage | en_US |
dc.subject | Hashing | en_US |
dc.subject | Cryptography | en_US |
dc.subject | Deep learning | en_US |
dc.subject | CNN | en_US |
dc.subject.lcsh | Traffic signs and signals. | |
dc.subject.lcsh | Blockchains (Databases) | |
dc.title | Blockchain-based traffic surveillance footage authenticity detection system | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, Brac University | |
dc.description.degree | B.Sc. in Computer Science | |